Analyze trading, client, market and transaction data to generate actionable business insights
Build predictive models for client churn, trading activity, cross-sell, and revenue forecasting
Develop risk, fraud, and anomaly detection models for surveillance and compliance
Perform time - series analysis on market data, volumes, and price movements
Support pricing, brokerage optimization, and margin analysis
Collaborate with business, risk, compliance, and technology teams
Design analytical frameworks for client segmentation and personalization
Create dashboards and reports for leadership using data visualization tools
Ensure data quality, governance, and adherence to regulatory norms
Continuously improve models based on business performance and market conditions
Key Competencies:
Strong proficiency in Python or R for data analysis and modelling
Experience with SQL and relational databases
Solid understanding of statistics, probability and linear algebra
Hands-on experience with machine learning algorithms
Experience using libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch
Data visualization experience using Matplotlib, Seaborn, Tableau
Ability to translate business problems into analytical solutions
Strong communication and stakeholder management skills
Stock broking / AMC knowledge preferred
Job Classification
Industry: Financial Services (Broking)Functional Area / Department: Data Science & AnalyticsRole Category: Business Intelligence & AnalyticsRole: Data AnalystEmployement Type: Full time