Data Scientist

We are looking for a driven and detail-oriented Data Analyst / Data Scientist with strong expertise in SQL, Python, Dashboarding, Data Automation, and BFSI Analytics. The ideal candidate should be capable of transforming large datasets into actionable business insights, automating reporting workflows, and building machine learning models to support business decision-making.

Responsibilities:

• Design and maintain interactive dashboards using Power BI, Tableau, or similar BI tools.
• Write complex SQL queries for data extraction, validation, transformation, and reconciliation.
• Develop Python-based automation scripts for reporting and data processing.
• Perform exploratory data analysis to identify trends, patterns, and business drivers.
• Build and validate machine learning models including Regression, Classification, Forecasting, Clustering, Customer Segmentation, and Anomaly Detection.
• Create model monitoring reports and track model performance metrics.
• Collaborate with business, risk, operations, collections, and technology teams to deliver actionable insights.
• Present analytical findings and recommendations to both technical and non-technical stakeholders.

Requirements:

• 1-5 years of experience in Analytics, Business Intelligence, or Data Science roles, preferably in BFSI / NBFC / Fintech environments.
• Strong hands-on experience in SQL and Python.
• Experience with Power BI, Tableau, or similar dashboarding tools.
• Good understanding of Statistics, Hypothesis Testing, Correlation Analysis, Sampling, and Trend Analysis.
• Working knowledge of Machine Learning techniques including Regression, Classification, Clustering, Forecasting, and Feature Engineering.
• Experience working with AWS Redshift and large-scale data warehouses.
• Hands-on experience in ETL Automation, Data Quality Checks, and Reporting Automation.
• Strong understanding of Data Analysis and Business Intelligence concepts.

Preferred Skills:

• Experience in BFSI Analytics, Risk Analytics, Collections Analytics, Customer Analytics, or Portfolio Monitoring.
• Exposure to Customer Segmentation, Propensity Modelling, Forecasting, and Anomaly Detection.
• Familiarity with Scikit-Learn, Statsmodels, and Model Validation Techniques.
• Knowledge of JIRA, Confluence, and Analytics Documentation Practices.
• Experience translating business problems into analytical solutions.

Skills

ML, Python, SQL, Machine Learning, Scikit-learn, Sklearn