Senior Data Scientist- Conversational AI

MISSION

Retail Investors across the world are ready to build wealth, but lack research & advice they can trust. StockGro is fixing that.

As India's leading stock market advisory and research platform, StockGro connect 35M+ users with 150+ SEBI-registered experts and our proprietary Stoxo AI. On our platform, users access research-backed trade ideas and turn complex stock market data into simple, actionable insights; facilitating research, backtesting and trade execution on one platform. We are also expanding our intelligent investing infrastructure across GCC, starting with the UAE.

We were featured among CB Insights Top 100 Fintechs globally (2023) and highlighted by the World Economic Forum (2026) for driving financial inclusion through AI (2026).

ABOUT STOCKGRO

Founded in 2020 by Ajay Lakhotia (former VC and seasoned entrepreneur), StockGro set out to solve a fundamental gap: making trusted, high-quality investment advice accessible to everyone. Today, we are India's largest stock market advisory and research platform, empowering over 35 million users to invest smartly.

Backed by Global Leaders

We have raised $110M from marquee investors including BITKRAFT Ventures, General Catalyst, SBI Investments (Japan), and Roots Ventures, with early backing from angels like Kunal Shah, Vivekananda Hallekere, and Rahul Garg.

Driven by High-Density Talent

Our team includes senior leaders from Sequoia, Swiggy, Glance, Airtel, and Uber, alongside alumni from ISB, the IIMs, and the NITs. Together, we are building an AI-powered investment intelligence stack and scaling our footprint across the GCC to make smart investments universally accessible.

Why Join Us

You will work on hard, meaningful problems that help generations build wealth. We move fast, think clearly, and give you complete ownership to build products that transform lives for millions of global investors.

What you'll work on:

• Building and owning a conversational AI research assistant for retail investors in Indian capital markets, think Claude but specialized for different instruments and macro analysis for non-expert users
• Designing multi-agent agentic pipelines with tool-calling, memory management, and multi-turn conversational flows that handle real, messy, incomplete queries from retail users (not just clean, structured prompts from analysts)
• RAG pipeline architecture: source curation, chunking strategy, embedding quality, retrieval tuning, reranking, and citation-grounded responses that retail users can trust
• Integrating real-time financial data sources (NSE/BSE feeds, Screener, Tickertape, news APIs, company filings) as live tool-callable data layers, not just static retrieval
• Building the guardrails and evaluation layer: domain scoping, hallucination mitigation, confidence scoring, and monitoring to ensure the system stays accurate and within bounds over time
• Fine-tuning or adapting LLMs where retrieval alone isn't sufficient
• Building ML models for user behaviour, personalization, and financial insights that feed into the conversational layer

• Expectations :

• Understanding of large language models (LLMs) like LLAMA, Anthropic Claude 3, or Sonnet.
• Familiarity with cloud platforms for data science like AWS Bedrock and GCP Vertex AI
• Strong proficiency in Python and data science libraries (scikit-learn, TensorFlow, PyTorch).
• Solid understanding of statistical methods, machine learning algorithms, and wealth tech applications.
• Experience in data wrangling, visualization, and analysis.
• Collaborative mindset and ability to thrive in a fast-paced startup environment.

• Bonus points:

• Experience in capital market usecases
• Familiarity with recommender systems and personalization techniques.
• Experience building and deploying production models.
• Data science project portfolio or contributions to open-source libraries.
• Experience with embedding models and retrieval quality improvement
• Worked at an AI-first startup in any domain