Lead Data Scientist

Angel One; Bengaluru; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Angel One, a leading Indian fintech, seeks a Lead Data Scientist to solve complex business problems using classical analytics, deep learning, and Generative AI. You will collaborate with product, marketing, engineering, and leadership to advance Angel One's growth through hands-on analytics initiatives and scalable ML solutions.

The role demands 6+ years of experience in data science, strong Python/SQL skills, and expertise in DL frameworks, NLP, and recommender systems.

Qualifications

• 6+ years of data science experience in fintech, trading, banking or e-commerce.
• Proven ability to build classical ML and deep learning models for business problems.
• Hands-on with Python, SQL and ML frameworks (TensorFlow, PyTorch).
• Experience with Generative AI and large language models (LLMs).
• Strong NLP and chatbot development capabilities.
• Excellent data visualization and communication skills.
• Master's or PhD in a quantitative field is preferred.

Responsibilities

• Develop and deployment of user quality scoring models using classical and DL methods.
• Build predictive models for customer lifetime value and churn.
• Design NLP-driven chatbots and conversational AI for product support.
• Create recommender systems using embedding techniques and collaborative filtering.
• Lead cross-functional analytics initiatives with product and marketing teams.
• Apply time-series and market analytics to predict user trading behaviors.
• Drive performance marketing optimization with ML-based experimentation.

Skills

Python

SQL

TensorFlow

PyTorch

Gen AI/LLMs

NLP

Time-series

ML/DL

Data Visualization

Education

Bachelor CS

Master's preferred

Tools

Tableau

Power BI

HuggingFace

OpenAI API

Job description

Angel One is one of India’s fastest growing fin-techs, on a bold mission to make investing simple, smart, and inclusive for every Indian. With over 3+ crore clients, we’re 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.

We’re a builder’s company at heart. You’ll 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. Everyone’s got a seat at the table and a shot to build something that lasts.

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

Job Title: Lead Data Scientist

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 One's growth through advanced, hands-on analytics and machine learning initiatives.

Key Problem Areas You'll 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.

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, Master's (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.