Lead Data Scientist

About Angel One :

Angel One is one of Indias fastest growing fin-techs, on a bold mission to make investing simple, smart, and inclusive for every Indian. With over 3+ crore clients, were building at scale – and building for impact.

Our Super App helps clients manage their investments, trade seamlessly, and access financial tools tailored to their goals. We are working to build personalized financial journeys for our clients, powered by new-age tech, AI, Machine Learning and Data Science.

Were a builders company at heart. Youll have the space to experiment, the freedom to move with velocity, and the mandate to make bold, user-first decisions – every single day.

The vibe Think less hierarchy, more momentum. Everyones got a seat at the table and a shot to build something that lasts.

Be part of a team thats moving fast, thinking big, and building for the next billion.

Job Title: Lead Data Scientist

Location: Bengaluru, Karnataka

Role Overview:

As a Lead Data Scientist, you will leverage your expertise in classical modeling, deep neural networks, and Generative AI/LLMs to solve complex, data-intensive business problems. You will collaborate closely with product, marketing, engineering, and leadership teams, significantly contributing to Angel Ones growth through advanced, hands-on analytics and machine learning initiatives.

Key Problem Areas Youll Tackle:

• Develop and enhance User Quality Scoring models using classical statistical methods and deep learning architectures.
• Build robust predictive models to estimate Customer Lifetime Value (LTV) utilizing deep neural networks and classical regression techniques.
• Design and implement predictive analytics solutions, including sequential deep learning models (e.g., LSTM, GRU) to accurately forecast User Churn based on user behavioral data.
• Engineer personalized Product and Feature Recommendation systems employing deep neural network embedding techniques and collaborative filtering methods.
• Leverage analytics and classical machine learning techniques for strategic Cross-Selling and Up-Selling of financial products.
• Create predictive frameworks assessing Loan Risk and Recoverability using advanced statistical modeling and deep learning techniques.
• Develop sophisticated NLP-driven Chat Bots using Generative AI/LLM models for improved customer interactions across product support, recommendations, pre-sales, and FAQs.
• Apply classical time-series modeling, deep learning, and Generative AI to predict and interpret User Trading Behaviors based on market analytics, macroeconomic trends, and news sentiment.
• Segment and classify users based on their App Interactions and Behavioral Patterns, integrating classical clustering methods and deep neural classification models.
• Optimize and fine-tune Performance Marketing Campaigns using deep neural networks, classical model optimization, and Generative AI-driven experimentation for scalable user acquisition.

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Required Skills & Qualifications:

• Technical Expertise: Demonstrated hands-on proficiency in Python, SQL, machine learning frameworks (TensorFlow, PyTorch), Generative AI (e.g., OpenAI, Hugging Face), and classical analytics tools.
• Deep Learning & Gen AI: Proven experience in building deep neural network models (CNN, RNN, Transformers) and leveraging Generative AI / Large Language Models (LLMs) for NLP and predictive analytics.
• Predictive Modeling: Strong background in classical statistical modeling and machine learning techniques (regression, clustering, classification).
• NLP & Chatbot Development: Hands-on experience developing and deploying NLP models and conversational AI solutions.
• Marketing Analytics: Deep understanding of digital marketing strategies, performance optimization, and customer acquisition analytics using classical and neural network models.
• Data Visualization & Reporting: Ability to clearly communicate analytical insights through intuitive visualizations (Tableau, Power BI, etc.).
• Analytical Thinking: Strong analytical mindset with the capability to transform complex datasets into actionable insights.
• Educational Background: Bachelors in Computer Science, Masters (preferred) or PhD in Statistics, Computer Science, Mathematics, Economics, or related quantitative field.
• Professional Experience: Minimum of 6+ years of experience in data science, predictive analytics, or related fields, preferably within fintech, trading, banking, or e-commerce sectors, with demonstrated hands-on experience in classical models, deep learning, and Generative AI applications.