Lead Decision Scientist

Lead Data Scientist with

Key Responsibilities:

1. Predictive & Prescriptive Modeling

• Design, develop, and deploy advanced models including. Have worked on or have some knowledge of-

• Optimization models

  : Solver-based (SLS-QP), Linear/Integer Programming

• Scoring models

  : Garrett Scoring, Decile Scoring, Similarity Scoring

• Forecasting models

  : ARIMA, Prophet, Exponential Smoothing

• Demand models

  : Demand Transference, Price Elasticity, Uplift Modeling

• Clustering & segmentation

  : K-Means, DBSCAN, Hierarchical Clustering

• Recommendation systems

  : Collaborative Filtering, Matrix Factorization

2. Proficiency in Agentic AI models & LLMs

• Apply and experiment with cutting-edge generative AI techniques:

• RAG (Retrieval-Augmented Generation)

• Agentic AI systems

  for autonomous decision-making

• LLM fine-tuning and prompt engineering

• Vector embeddings and similarity search

• Knowledge Graphs and semantic search

• Synthetic data generation

  for model training and testing

• Multi-modal AI

  (text, image, tabular fusion)

3. Data Engineering & Infrastructure & MLOPS

• Collaborate with data engineering teams to ensure robust data pipelines:
• ETL design and orchestration
• Data harmonization and schema alignment, Data Validation
• Data cleaning, validation, and enrichment
• Feature engineering and transformation pipelines

4. Business Integration & Product Collaboration

• Translate business objectives into analytical frameworks and models.
• Work closely with product managers, SMEs, and engineers to integrate models into product features.
• Contribute to MVP planning, experimentation, and agile delivery cycles.
• Support A/B testing, KPI tracking, and model performance monitoring.

Required Skills & Experience:

• 8-12 years of experience in data science, preferably in CPG, Retail analytics, or SaaS environments.
• Some experience with generative AI frameworks and LLM-based applications.
• Proficiency in Agentic AI, Open AI API’s, Langchain, Langgraph, Crew AI or similar frameworks
• Understanding of training Agents, Tools Integration using MCP and Agentic Prompt Engineering
• Familiarity with cloud platforms (AWS, GCP, Azure) and MLOps practices.

Preferred Qualifications:

• Experience in CPG, Retail analytics, or consumer behavior modelling.
• Exposure to Gen AI frameworks like Langchain, Langgraph, CrewAI
• Good understanding of Gen AI modelling, Validation of Agents, Guardrails
• Strong communication skills and ability to present insights to technical and non-technical stakeholders.