companyOptasia logo

Junior Quantitative Risk Data Scientist at Optasia | Athens, Greece

OptasiaAthens, Attica, Greece
On-site Full-time

Clicking Apply Now takes you to AutoApply where you can tailor your resume and apply.


Unlock Your Potential

Generate Job-Optimized Resume

One Click And Our AI Optimizes Your Resume to Match The Job Description.

Is Your Resume Optimized For This Role?

Find Out If You're Highlighting The Right Skills And Fix What's Missing

Experience Level

Entry Level

Qualifications

Bachelor’s degree in Data Science, Statistics, Mathematics, or a related discipline. Strong background in statistical modeling; familiarity with machine learning is advantageous. Proficient in programming languages such as Python or R, with substantial experience in big data analytics. Thorough understanding of risk analytics and credit risk determinants. Adept at managing and analyzing large datasets to extract valuable insights. Excellent analytical and problem-solving abilities.

About the job

Optasia is an innovative B2B2X financial technology platform dedicated to transforming financial decision-making, scoring, disbursement, and collection processes. Our mission is to promote financial inclusion for everyone, and we are making a significant impact in the world.

We are looking for passionate individuals who are driven by results and possess a proactive mindset. Join our dynamic team of like-minded professionals who are committed to delivering cutting-edge solutions in an exciting and collaborative environment.
As a Junior Quantitative Risk Data Scientist, you will play a vital role in enhancing Optasia's advanced risk management strategies and optimizing revenue as a key member of our Credit Portfolio Optimization team. This team specializes in credit scoring, model development, and managing large loan portfolios daily. Your responsibilities will include (i) creating statistical and machine learning algorithms for credit evaluation, (ii) optimizing revenues through effective risk management, (iii) conducting detailed risk analytics, and (iv) integrating models into day-to-day operations of extensive loan portfolios. You will collaborate within a robust team of 25 skilled professionals.

Your Responsibilities

  • Conduct comprehensive risk analyses and optimizations on microloans, comprising 80% of your role.
  • Design predictive models, primarily focusing on statistical approaches with occasional machine learning applications.
  • Provide actionable insights into credit risk utilizing advanced big data analytics.
  • Assess and analyze credit risk factors through computational techniques on extensive datasets.
  • Work closely with cross-functional teams to facilitate data-driven decision-making.
  • Continuously enhance risk models to maximize financial outcomes while minimizing risks.

Your Qualifications

  • Bachelor’s degree in Data Science, Statistics, Mathematics, or a related discipline.
  • Strong background in statistical modeling; familiarity with machine learning is advantageous.
  • Proficient in programming languages such as Python or R, with substantial experience in big data analytics.
  • Thorough understanding of risk analytics and credit risk determinants.
  • Adept at managing and analyzing large datasets to extract valuable insights.
  • Excellent analytical and problem-solving abilities.

Key Attributes

  • Exceptional interpersonal and communication skills.
  • Capacity to meet tight deadlines while maintaining meticulous attention to detail.
  • Strong judgment and problem-solving capabilities.
  • Experience adhering to secure coding practices and guidelines (e.g., OWASP, NIST).

Why Join Us? Experience the thrill of working in a forward-thinking company that is committed to driving change in the financial landscape.

About Optasia

Optasia is pioneering a comprehensive B2B2X financial technology platform aimed at enhancing scoring, financial decisioning, disbursement, and collection processes, focusing on enabling financial inclusion for all.

Similar jobs

Tailoring 0 resumes

We'll move completed jobs to Ready to Apply automatically.