Key Responsibilities

- Strategic Planning: Define the 3-year vision, roadmap, and architecture for

Data Science, Machine Learning, and AI within the brokerage ecosystem.
- AI & Machine Learning Leadership: Lead the development of advanced ML models, Natural Language Processing (NLP) solutions, and Generative AI applications for market research, sentiment analysis, client onboarding, and automated insights.
- Product Collaboration: Work closely with Product, Risk, Tech, and Trading

Operations teams to deploy scalable data products that improve user retention, trade volume, risk management, and portfolio personalization.
- Data Engineering & Infrastructure: Oversee data lakehouse architectures,

ETL pipelines, and real-time streaming architectures to handle high-

frequency market feeds, tick data, and transactional logs.

- Team Leadership & Mentorship: Hire, mentor, and manage a team of Data

Scientists, ML Engineers, and Data Analysts. Establish standards for code quality, MLOps, model monitoring, and governance.
- Governance & Regulatory Compliance: Ensure all quantitative models and

AI implementations comply with financial regulations, data privacy laws,



and model risk management standards.

Required Qualifications & Skills

- Experience: 7+ years of core data science, machine learning, and quantitative modeling experience, preferably in Stock Broking, Fintech,

Quantitative Finance, or Banking.
- Strategic Vision: Proven track record of translating business problems into data strategies and driving revenue or efficiency gains through quantitative models.
- NLP & Generative AI: Practical experience deploying NLP models for sentiment analysis on financial news/filings, chatbots, and unstructured financial text extraction.
- Core ML & Data Analytics: Solid command of Python, R, SQL, Machine

Learning frameworks (PyTorch, TensorFlow, Scikit-Learn), and advanced statistical analytics.
- Data Engineering & Cloud Infrastructure: Deep understanding of big data systems (Spark, Kafka, Snowflake/BigQuery) and MLOps platforms on

AWS, Azure, or GCP.

• Education: Masters or Ph.D. in Computer Science, Data Science, Statistics, Mathematics, Quantitative Finance, or a related field.

📌 Data Science Lead / Head of Data Science (2+ yrs) (Mumbai)
🏢 Spectrum
📍 Mumbai