IT / Data Science & Analytics / Data Scientist

We are looking for a strong Data Scientist who can turn complex data into clear business decisions.

This role sits at the intersection of data analytics, credit risk, product performance, and business strategy. You will work with large datasets, analyze customer and product behavior, support forecasting and scoring initiatives, and help business and technical teams make better decisions.

The ideal candidate is not only technically strong in SQL and analytics, but also able to think logically, challenge assumptions, explain insights clearly, and understand the business impact of every analysis.

• Analyze large datasets to answer real business questions and support decision-making.
• Build clear reports, conduct deep-dive analyses, and produce improvement recommendations.
• Identify trends, anomalies, risks, and opportunities in customer, product, and financial data.
• Develop forecasts and scenario analyses using clear assumptions and structured reasoning.
• Support credit scoring, risk segmentation, acceptance strategy, and portfolio performance analysis.
• Participate in scoring model development, testing, validation, and monitoring.
• Analyze bad debt, repayment behavior, customer acceptance, product profitability, and campaign performance.
• Evaluate business trade-offs between revenue growth, risk, bad debt, and profitability.
• Collaborate with business and technical teams during product launches, changes, and experiments.
• Translate business questions into analytical tasks, and translate analytical results back into simple business recommendations.
• Help improve data quality by identifying inconsistencies, missing data, anomalies, and root causes.
• Present findings clearly to both technical and non-technical stakeholders.
• Support and mentor junior team members when needed.

Must-Have Skills

• Strong SQL skills, including joins, aggregations, filtering, window functions, deduplication, and performance-aware querying.
• Ability to work with large datasets and structure analytical logic clearly.
• Strong analytical thinking and problem-solving skills.
• Good understanding of statistics, probability, and basic machine learning concepts.
• Ability to make reasonable assumptions, estimate outcomes, and explain the logic behind calculations.
• Ability to connect analysis with business impact, especially revenue, risk, profitability, and customer behavior.
• Clear communication skills: ability to explain complex ideas in simple language.
• Attention to detail and ability to validate your own work.
• Working proficiency in English and ability to communicate with team members in Russian or Azerbaijani.

Technical Skills

• Advanced SQL.
• Python and/or C# for analysis, automation, data processing, or model support.
• Experience with reporting, analytical datasets, and business performance tracking.
• Understanding of forecasting, segmentation, scoring models, or risk analytics.
• Familiarity with data quality checks, anomaly detection, and root-cause analysis.

Nice to Have

• Experience in credit risk, fintech, telecom, lending, microfinance, or digital financial services.
• Experience with scorecards, risk models, acceptance strategies, or bad debt analysis.
• Experience with A/B testing, pilot monitoring, or model comparison.
• Experience with dashboarding or BI tools.
• Experience mentoring analysts or leading analytical workstreams.