Data Scientist - Production Grade Machine Learning

Join Vortexa, a leader in the energy data analytics sector, as a Data Scientist specializing in production-grade machine learning. In this role, you will harness the power of advanced algorithms to process thousands of energy data points per second from diverse operational sources. Your expertise will be crucial in managing vast datasets while implementing sophisticated classification and anomaly detection models in real-time. You will maintain comprehensive data lineage and deliver actionable insights through high-performance platforms utilized by energy operators around the world.As a member of the Data Platform Team, you will oversee all machine learning operations across our extensive energy data ecosystem. Your work will span from raw sensor data from millions of energy assets to complex operational datasets, generating high-value predictions such as equipment failure detection, energy demand forecasting, operational anomaly identification, predictive maintenance scheduling, and system optimization recommendations.We pride ourselves on developing a robust suite of statistical and machine learning models that provide the most precise and actionable insights into energy operations. Our models are continuously validated by in-house energy analysts and traders, ensuring the reliability of our predictions. You will play a key role in designing and building ML infrastructure and applications that enhance the design, deployment, and monitoring of ML pipelines and models.Collaborating closely with software engineers, fellow data scientists, and energy analysts, you will help bridge the gap between research experiments and production energy systems, ensuring operational uptime and fault tolerance of our ML platform.

About WheelyWheely is at the forefront of revolutionizing premium transportation across major cities in Europe, the US, and the Middle East. We integrate advanced technology with the art of five-star chauffeuring, providing an experience trusted by over 100,000 active riders and 1,200 corporate partners.As a profitable and rapidly growing scale-up, we have raised $43M and generated over $100M in annual revenue. With our recent expansion into New York City, we are accelerating our growth across the US and EMEA. If you are passionate about your craft and eager to help shape the next phase of our journey, we invite you to connect with us.We are looking for mid-level and senior Data Scientists / Machine Learning Engineers who will take ownership of the entire workflow, from ideation and research to production deployment.Join one of our specialized teams (Mapping, Matching, Pricing, or Supply) to tackle complex and high-impact challenges such as ETA prediction, routing, map matching, dynamic pricing, bipartite matching, driving style prediction, and LLM integration.

At Intercom, we are revolutionizing customer service through artificial intelligence, empowering businesses to deliver outstanding customer experiences.Our AI agent, Fin, stands as the most sophisticated customer service AI agent available, allowing companies to provide continuous, flawless customer support, ultimately enhancing customer interactions. Fin seamlessly integrates with our Helpdesk to form the Intercom Customer Service Suite—a comprehensive solution that offers AI-augmented assistance for more complex or high-touch inquiries that necessitate human intervention.Since our inception in 2011, Intercom has earned the trust of nearly 30,000 businesses worldwide and is setting a new benchmark in customer service. Guided by our core values, we consistently push boundaries, work with speed and intensity, and deliver exceptional value to our clients.What’s the Opportunity?The Machine Learning team at Intercom is tasked with defining innovative ML features, researching suitable algorithms and technologies, and quickly delivering initial prototypes to our customers.Our team is deeply product-focused, collaborating closely with Product and Design teams. Our dedicated ML product engineers enable rapid transitions to production, often launching beta versions just weeks after successful offline testing.We are passionate about harnessing machine learning technology, having productized everything from traditional supervised models to cutting-edge unsupervised clustering algorithms and novel transformer neural network applications. We rigorously evaluate the real customer impact of each model we deploy.What Will I Be Doing?Identifying opportunities where machine learning can add value for our customers.Defining the appropriate ML framing for product challenges.Collaborating with teammates and stakeholders from Product and Design.Conducting exploratory data analysis and research.Gaining a deep understanding of the problem areas.Researching and selecting the most suitable algorithms and tools.Being pragmatic while pushing the boundaries of innovation when necessary.Performing offline evaluations to validate algorithm effectiveness.Working alongside engineers to transition prototypes into production.Planning, measuring, and sharing insights to guide iterative development.Collaborating closely with the team and others to create exceptional ML products.

Isomorphic Labs is pioneering the application of advanced AI technologies to unlock profound scientific insights, expedite breakthroughs, and develop transformative medicines with a vision to eradicate all diseases.The future is on the horizon, made possible by the remarkable capabilities of machine learning. We envision a world where diseases are effectively managed or eliminated through accelerated and enhanced drug discovery.Join our interdisciplinary team to spearhead groundbreaking innovations and play a pivotal role in our mission to achieve ambitious health-related goals, all while contributing to a vibrant and collaborative workplace culture.The future we aspire to is being shaped today. It begins with our culture at Isomorphic Labs. It starts with you.About Isomorphic LabsFounded in 2021, Isomorphic Labs (IsoLabs) strives to enhance human health by building upon the Nobel Prize-winning AlphaFold system. Our diverse team of experts in drug discovery and machine learning has developed groundbreaking predictive and generative AI models that accelerate scientific discovery at an unprecedented pace.Our name reflects our belief in the inherent symmetry between biology and information science. By leveraging AI's robust capabilities, we can model complex biological processes to design innovative molecules, predict drug performance, and develop novel treatments for some of the world's most challenging diseases.Our state-of-the-art drug design engine integrates AI models capable of addressing various therapeutic areas and drug modalities. We are dedicated to continuously innovating model architectures and creating cutting-edge solutions to advance rational drug design.With each significant advancement, we are progressing towards the promise of digital biology, moving closer to our ambitious mission of ultimately solving all diseases through the power of AI.

Intercom is an innovative AI Customer Service company dedicated to empowering businesses to deliver exceptional customer experiences.Our state-of-the-art AI agent, Fin, is recognized as the leading customer service AI solution available. It enables businesses to provide consistent, high-quality customer service, thereby enhancing their overall customer experience. Fin can seamlessly integrate with our Helpdesk to form the comprehensive Intercom Customer Service Suite, which offers AI-enhanced support for more complex queries that necessitate human intervention.Founded in 2011 and trusted by nearly 30,000 businesses worldwide, Intercom is redefining the customer service landscape. Guided by our core values, we continuously challenge the status quo, act with urgency, and strive to deliver remarkable value to our clients.What is the Opportunity?Our Machine Learning team at Intercom is pivotal in identifying and developing new ML features, exploring suitable algorithms and technologies, and swiftly delivering initial prototypes to our customers.We are a highly product-focused team, collaborating closely with our Product and Design partners. The dedicated ML product engineers on our team enable us to expedite our transition to production, often launching beta versions just weeks after successful offline testing.We are deeply passionate about harnessing machine learning technology, having productized a range from traditional supervised models to state-of-the-art unsupervised clustering algorithms and innovative applications of transformer neural networks. We rigorously test and evaluate the tangible customer impact of each model we deploy.What Will I Be Doing?Actively participate in recruitment, mentoring, and career development initiatives for fellow engineers.Elevate technical standards, performance metrics, reliability, and operational excellence.Pinpoint opportunities where ML can deliver significant value to our customers.Collaborate with team members and Product and Design stakeholders to define the appropriate ML framework for product challenges.Conduct exploratory data analysis and research to gain a deep understanding of the problem domain.Investigate and select suitable algorithms and tools, balancing practicality with cutting-edge innovation where necessary.Execute offline evaluations to validate algorithm efficacy.Collaborate with engineers to transition prototypes to production.Plan, measure, and disseminate insights to guide iterative improvements.

Wise seeks a Lead Machine Learning Engineer / Scientist based in London. This role centers on developing and refining machine learning models and algorithms that help drive data-informed decisions throughout the company. What you will do Build and enhance machine learning models to support Wise’s products and services. Collaborate with teams from various disciplines to deliver scalable, effective solutions. Apply advanced algorithms to improve decision-making and strengthen product offerings. Collaboration This position involves working closely with colleagues across the business, bringing together expertise from different areas to solve complex challenges and deliver impactful results.

Join our dynamic team at Trainline as a Data Scientist, where you will leverage data to drive insights and influence strategic decisions. You will work with cross-functional teams to develop models that enhance our customer experience and optimize our operations. If you have a passion for data and want to make a real impact in the travel industry, this is the opportunity for you!

Join Ravelin, the forefront of fraud detection technology! We leverage cutting-edge machine learning and network analysis to tackle significant challenges in online transaction security. Our mission is to ensure that online transactions are safe, allowing our clients to confidently serve their customers.We believe in fostering a vibrant workplace culture characterized by empathy, ambition, unity, and integrity. At Ravelin, we emphasize work-life balance and maintain a flat hierarchy across the company. By becoming part of our team, you will quickly gain insights into the latest technologies while collaborating with some of the brightest minds in the industry. Check out our Glassdoor reviews!If you resonate with our values and enthusiasm for preventing fraud, we encourage you to explore our blog to see how you can contribute to safeguarding the world's largest online businesses.The RoleWe are excited to welcome a Junior Data Scientist to our dynamic team of client-facing data scientists and support analysts. In this pivotal role, you will delve into client data to uncover patterns and trends related to fraud. By applying exploratory analysis, you will create meaningful narratives from data, probing not just “what” and “how” but also “why.” Your interactions with clients will be crucial in helping them understand their fraud landscape and refining our focus on targeted solutions.ResponsibilitiesEngage directly with clients to deliver insights from fraud analytics and machine learning models.Examine large datasets to pinpoint fraud patterns, trends, and emerging threats, enhancing client outcomes.Collaborate with clients to address specific fraud challenges, developing effective and innovative solutions.Compile reports and present analytical findings to clients as needed.Identify new model features and enhance model efficacy.Optimize graph network performance through network analysis.Gain practical experience with our cloud infrastructure and utilize available tools to enhance client data and performance.Develop internal tools in Python to improve our analytical abilities.

Join our dynamic team at Faculty as a Data Scientist, where your analytical prowess will help drive impactful decisions across various sectors. In this role, you'll leverage advanced statistical techniques and machine learning algorithms to extract insights from complex datasets, delivering actionable recommendations to stakeholders. Collaborate with cross-functional teams to innovate and optimize data-driven solutions that enhance our clients' operational efficiency.

Join Perplexity, a cutting-edge company serving millions of users each day with high-quality answers powered by an LLM-first search engine and specialized data sources. We strive to leverage the latest models as they become available, navigating the complexities of the intelligence frontier where traditional benchmarks may fall short. In this pivotal role, you will be responsible for creating specialized evaluations aimed at enhancing answer quality across Perplexity, specifically focusing on search-based LLM responses and other user-favored scenarios.ResponsibilitiesDesign and manage automated evaluation pipelines that measure answer quality across Perplexity's products, ensuring adherence to high standards of accuracy and usefulness.Create tailored evaluation datasets and methodologies to assess the influence of tool calls, particularly in web search retrieval, on the quality of final answers.Develop VLM-based solutions to programmatically analyze the visual rendering of final answers across various platforms and devices.Consistently evaluate public benchmarks and academic assessments for their relevance to Perplexity's offerings, adapting and integrating them into our ongoing performance evaluations.Collaborate within a small, high-impact team where your evaluation metrics will directly influence product enhancements, working closely with technical leadership to measure and elevate Answer Quality.QualificationsPhD or MS in a technical discipline or equivalent practical experience.A minimum of 4 years of experience in data science or machine learning.Proficient in Python and SQL, with the ability to write production-quality code.Experience with modern cloud data stacks, particularly AWS and Databricks.Familiarity with agentic coding workflows and utilizing AI-assisted development tools for efficient iteration.Preferred QualificationsAt least 1 year of experience working with LLMs at scale, especially in LLM-as-a-judge configurations.Experience developing customer-facing web products or consumer applications with significant user traffic.A robust research background, demonstrating the application of research methodologies to real-world machine learning challenges.Experience in defining evaluation metrics, such as factual consistency, hallucination rate, and retrieval precision, along with creating ground truth datasets.

Are you ready to drive change? Join AnyVan and transform the way we move anything, anywhere. Here, you can build a fast-paced career that matches our innovative approach to logistics.Founded in 2009 by our visionary CEO Angus, AnyVan was born from a simple observation: too many vans were on the road half-empty. We set out to revolutionize logistics technology, aiming to reduce wasted miles by efficiently filling those empty spaces.Today, we proudly serve over 5 million customers across the UK and Europe, supported by a dedicated team of 400 AnyVanners based in London, Cape Town, and Bogota. Together, we are committed to making a difference by saving 8,520 tonnes of carbon emissions annually.At the heart of our rapidly growing logistics marketplace is a dynamic interplay of supply, demand, and the customers eager to receive their belongings.This is where you come in.We are seeking a Senior Pricing Data Scientist—a professional who blends data science, economics, and storytelling to create models that elegantly manage complex systems.If you're passionate about transforming chaotic marketplaces into well-functioning systems, we want you to shape our pricing engines, conduct adaptive experiments, develop new data science products, and articulate complex insights into impactful narratives for the business.If you're excited about driving impact through experimentation, refining state-of-the-art pricing models, and tackling high-stakes challenges, come take the wheel! Key Responsibilities: Develop and Enhance ML Pricing Engines Craft and implement innovative pricing models that empower AnyVan to make informed decisions and foster a thriving marketplace. Conduct Adaptive Experiments Deploy systems that learn dynamically from customer behaviors, ensuring our pricing adapts to the ever-evolving marketplace. Innovate Data Science Products Identify opportunities, devise solutions, and deliver tools that elevate business processes and make data indispensable. Communicate Complex Insights Clearly Transform intricate models into engaging, impactful narratives for stakeholders.

About LendableLendable is on an ambitious journey to create the world's leading technology for enabling access to credit and facilitating savings. We are rapidly emerging as one of the foremost fintech firms globally, with a remarkable trajectory:Recognized as one of the UK's newest unicorns, our talented team exceeds 700 individuals.We are among the fastest-growing tech companies in the UK.Achieved profitability since 2017.Supported by prestigious investors such as Balderton Capital and Goldman Sachs.Adored by customers, boasting top reviews (4.9 stars across thousands of reviews on Trustpilot).To date, we have reimagined the Big Three consumer finance products from the ground up: loans, credit cards, and car finance. Our innovative approach ensures that customers receive funds within minutes instead of days.With our rapid growth, we are poised to tackle the two largest Western markets (UK and US), where vast financial assets are managed by traditional banks with outdated systems and cumbersome processes.Why Join Us?Embrace ownership across diverse responsibilities. From day one, you will have the autonomy to make impactful decisions that shape Lendable's success.Collaborate with exceptional teams who are committed to resourcefulness in solving problems and developing innovative solutions.Develop cutting-edge technology in-house, utilizing advanced data sources, machine learning, and AI to optimize our processes.About the RoleWe are thrilled to welcome a new Data Scientist to our dynamic team! As a leader in real rate risk-based pricing, Lendable provides consumers with clear insights and product assurance during the application process. Data Science is integral to this unique selling proposition, crafting robust credit risk models for our loan and credit card offerings.You will leverage the latest machine learning methodologies alongside a comprehensive data repository to construct market-leading risk models.

About ZegoAt Zego, we believe that traditional motor insurance can be a barrier for exemplary drivers. It's often too complex, costly, and fails to accurately reflect real driving behavior.Since our inception in 2016, we've dedicated ourselves to transforming the insurance landscape. Our goal is to provide the most affordable insurance options for responsible drivers.Our diverse clientele, ranging from van drivers and gig economy workers to everyday car owners, is at the core of our operations.Having successfully sold tens of millions of policies and secured over $200 million in funding, we are just getting started on this exciting journey.Your RoleWe are in search of a Lead Data Scientist to join our Core Pricing team, reporting directly to the Head of Data Science. You will play a critical role in shaping and executing a high-performance data-science operating model, swiftly transforming concepts into production-ready pricing and risk models.Key ResponsibilitiesLead the development and enhancement of next-generation risk models, managing all aspects from innovative feature discovery and sophisticated modeling to dependable pipeline deployment and strategic R&D initiatives.Implement a robust Data Science workflow: ensuring clear guidelines, templates, and documentation throughout the project lifecycle.Accelerate the idea-to-production timeline: from initial data acquisition to live rate adjustments.Promote a culture of collaborative experimentation: integrating Pricing, Data Science, Machine Learning Engineering, and Systems Engineering.Team leadership and mentorship: oversee a team of 2 Data Scientists, guiding their professional growth and development.Establish coding standards and best practices, mapping common processes and creating playbooks.Assist in selecting tools utilized throughout the Data Science project lifecycle.

Are you passionate about data and eager to drive innovation? Join Hudl as a Lead Data Scientist and take the reins in shaping data-driven strategies. In this role, you will leverage advanced analytics to enhance performance across various teams and projects, while mentoring junior data scientists to foster their growth.

Are you ready to elevate your career? At Almedia, we provide an unparalleled platform for ambitious professionals to thrive and advance at an accelerated pace. We are on a mission to establish ourselves as Germany’s premier bootstrapped unicorn and have already achieved the status of Europe’s third fastest-growing company as per the FT1000 in 2025.We're revolutionizing marketing by creating a unique ecosystem where our community of over 60 million users is rewarded for engaging with top-tier advertisers' products. This innovative approach is redefining user acquisition for the world's leading brands.Position Overview: Director of Machine LearningWe are seeking a dynamic Director of Machine Learning who possesses the ability to build innovative solutions from the ground up, delve deeply into technical aspects, and cultivate a robust, high-performing team. This is a hands-on leadership role where your expertise will be critical.Key ResponsibilitiesLead the entire ML roadmap, from identifying problems to implementing solutions in production environments.Design, develop, and deploy recommendation systems and other essential ML products.Engage in hands-on development: prototype, code, and iterate rapidly.Recruit and nurture a high-ownership ML team.Elevate technical standards across architecture, reviews, and strategic initiatives.QualificationsExtensive background in ML engineering with experience in scalable production systems.Proven experience in recommender systems, pricing strategies, advertising technologies, or related fields.Demonstrated ability to build new ML products or teams from zero to one.A strong track record of success within fast-paced, high-ownership startup environments.Why Choose Almedia?Join a scaling startup: Make a significant impact and grow with a company that has been profitable since its inception.Thriving Environment: We empower our staff to take ownership of projects, constantly striving to elevate performance.Rewarding Excellence: We offer a generous bonus scheme to recognize and reward proactive contributions.At Almedia, we are committed to nurturing talent, assessing diverse skill levels during recruitment, and providing clear pathways for professional growth. We are an equal opportunity employer and celebrate diversity, inviting individuals from all backgrounds to apply.

About Sylvera Sylvera empowers organizations to make informed investments in carbon and commodity markets. Our independent assessments of carbon project quality, market pricing, and supply signals, alongside our geospatial and carbon intensity data, provide clients with the vital insights needed for impactful climate action.Our diverse team of over 130 scientists, engineers, and market analysts operates across major cities including London, New York, São Paulo, Singapore, and Tokyo. We specialize in market intelligence, geospatial analytics, multi-scale lidar research, and policy analysis, partnering with governments to enhance transparency and rigor in carbon markets.With backing from over $96 million in investment from prominent firms like Fidelity, Balderton Capital, Index Ventures, and Insight Partners, we are trusted by Fortune 500 companies and major financial institutions globally.If you are passionate about climate science, enjoy tackling complex challenges, and wish to work with a dedicated team committed to our mission, we invite you to explore this opportunity.Role Overview ‍‍We are seeking a dedicated Applied Scientist – Forest Lidar & 3D ML to join our Earth Analytics (EA) team.Your primary focus will be to address a significant research challenge in a high-impact commercial context: the automation of tree segmentation from intricate terrestrial laser scanning (TLS) point clouds. Your work will be pivotal in enhancing Sylvera’s innovative Biomass Atlas product, which is increasingly utilized for carbon accounting within carbon markets. You will gain exclusive access to a premier ground-truth, labeled dataset of 3D forest point clouds sourced from global forests.Key Responsibilities:Designing, training, and implementing advanced 3D deep learning models (e.g., sparse convolutions, PointNet, TreeLearn, or similar architectures) for automating tree instance segmentation and Quantitative Structure Model (QSM) generation.Converting experimental machine learning research into reliable, reproducible code, collaborating closely with our production engineering team to deploy models at scale.

Join our innovative team at Helical as a Senior Computational Scientist, where your expertise in computational biology and machine learning will directly contribute to transformative drug discovery processes. You will play a pivotal role in bridging the gap between our foundational models and real-world applications, guiding model evaluations and practical use cases that address pressing challenges in drug development and translational research.As a respected senior individual contributor, you will report to the Head of Computational Biology, with ample opportunities for career advancement into management roles as our team expands. You will collaborate closely with our research team, providing mentorship to junior scientists and working in tandem with Product and Business Development to translate advanced biological concepts and machine learning techniques into impactful solutions for our clients.

Why Join Faculty?Founded in 2014, Faculty believes that artificial intelligence is the defining technology of our era. We have partnered with over 350 clients globally to revolutionize their operations through human-centered AI. Discover our tangible impacts here.We prioritize innovation over trends, developing and implementing responsible AI solutions that drive significant results. Our expertise spans technical, product, and delivery domains, serving clients in government, finance, retail, energy, life sciences, and defense sectors.As our company and reputation rapidly expand, we seek individuals who possess intellectual curiosity and aim to forge a positive technological legacy.Join us and explore the transformative potential of AI, empowered to realize its most impactful applications.About Our TeamOur Retail and Consumer specialists are committed to assisting clients in an industry undergoing rapid technological advancements and shifting consumer expectations. With over a decade of experience in Applied AI, we merge exceptional technical skills with delivery expertise, empowering businesses to adapt and excel.About the RoleIn the role of Lead Data Scientist, you will take on a crucial, entrepreneurial position as a technical expert who excels in navigating complexity and driving commercial impact. You will set the technical vision and guarantee the effective, scalable delivery of our most challenging, high-stakes projects. This role combines profound machine learning knowledge with strategic oversight, allowing you to define project roadmaps, manage technical risks, and architect dependable solutions. Your mission will be to spur innovation, mentor cross-functional teams, and actively influence our technical standards and long-term client relationships.Your Responsibilities:Establishing the technical direction for intricate, business-critical projects while adeptly managing trade-offs between speed, innovation, and reliability.Designing and executing robust, production-ready technical solutions.

CoreWeave is The Essential Cloud for AI™. Constructed for innovators by innovators, CoreWeave offers a cutting-edge platform filled with technology, tools, and expert teams that empower visionaries to create and expand AI solutions confidently. Renowned by top AI labs, startups, and global enterprises, CoreWeave merges exceptional infrastructure performance with profound technical knowledge to propel advancements and convert computational power into actionable capabilities. Established in 2017, CoreWeave became a publicly traded entity (Nasdaq: CRWV) in March 2025. Discover more at www.coreweave.com. We take pride in being a Living Wage accredited employer. What You’ll Do:The Monolith Data Science team is on a mission to develop a layered reliability platform that transitions CoreWeave from reactive troubleshooting to proactive reliability engineering. This platform encompasses telemetry ingestion, feature engineering, anomaly detection, failure prediction, and distributed straggler detection, alongside agentic root cause analysis. We work closely with Fleet, Infrastructure, and AI Platform teams to enhance cluster reliability, boost effective utilization (MFU), minimize MTTR, and safeguard uptime and revenue.About the role:As a Data Scientist, you will create sophisticated statistical models and machine learning strategies to maximize GPU utilization, optimize workload scheduling, and enhance infrastructure efficiency. You will design experiments, analyze extensive system telemetry data, and prototype predictive and optimization algorithms that directly influence production systems. This position marries rigorous research with tangible impact, transforming complex infrastructure data into quantifiable enhancements in performance and cost. You will work collaboratively across teams to convert research insights into applicable solutions.Who You Are:MS or PhD in Computer Science, Statistics, Applied Mathematics, Machine Learning, or a related quantitative field8+ years (or equivalent research experience) in implementing statistical modeling or machine learning on large-scale datasetsStrong proficiency in Python and scientific computing libraries (NumPy, pandas, SciPy, scikit-learn, PyTorch or TensorFlow)Proven experience designing and analyzing controlled experiments (A/B testing, causal inference, hypothesis testing)

About UsGreetings! We are Ravelin, a pioneering fraud detection firm leveraging state-of-the-art machine learning and network analysis technologies to tackle significant challenges. Our mission is to enhance the safety of online transactions, empowering our clients to serve their customers with confidence.We also believe in enjoying the journey! Our team is welcoming and we take pride in our vibrant culture, embodying values such as empathy, ambition, unity, and integrity. We emphasize a healthy work/life balance and embrace a flat organizational structure. Join us to quickly learn about cutting-edge technologies while collaborating with some of the brightest and kindest individuals - check our Glassdoor reviews!If this resonates with you, we are eager to connect! For further insights, visit our blog and discover how you can help us combat fraud and safeguard the world's leading online businesses.The TeamYou will be a vital part of the Detection team, dedicated to minimizing fraud rates and ensuring client satisfaction by continually training and deploying machine learning models. Our objective is to simplify model deployments to be as seamless and error-free as possible, adhering to Google's Best Practices for ML Engineering.Our models are expertly trained to identify various types of fraud in real-time, utilizing diverse data sources and techniques. Our prediction pipelines operate under strict SLAs, ensuring every prediction is delivered within 300ms. When models underperform, it is the Detection team's responsibility to investigate the issues.The Detection team is pivotal to Ravelin’s success, collaborating closely with the Data Engineering Team, who build the infrastructure, and the Intelligence & Investigations Team, who engage with our clients.The RoleWe are seeking a Data Scientist to train, deploy, debug, and evaluate our fraud detection models. The ideal candidate will be pragmatic, approachable, and equipped with insights gained from previous experiences.Assessing fraud models can be challenging; often, labels may not be available for up to three months. You will need to exercise your judgment when exploring ambiguous fraud cases and validating the efficacy of the models themselves.We strive to develop robust models capable of adapting their insights when exposed to new fraud tactics; our clients expect us to stay ahead of fraud trends. You will receive the tools, environment, and guidance necessary to create world-class fraud detection solutions.