Description

Lead data science initiatives across the end-to-end model lifecycle, from data exploration and feature engineering to training, validation, and deployment.

This role is on-site.

Responsibilities

• Lead use cases and workstreams with junior data scientists, guiding scope, design, and final reporting.
• Perform data wrangling, fuzzy matching, and ETL to prepare high-quality modeling datasets from various sources.
• Develop and validate ML models, applying clustering, decision trees, boosting, and neural networks while ensuring scalability.
• Package and deploy models in cooperation with Data Engineers and MLOps teams.
• Present insights using data visualization and communicate results clearly to decision-makers.

Required Skills

• 3+ years of hands-on ML modeling and development experience.
• Strong programming skills in Python.
• Solid understanding of data analysis, statistical modeling, and ML technique trade-offs.
• Hands-on experience with data wrangling, including fuzzy matching and regular expressions.
• Familiarity with NLP, LLMs, RAG architecture, and agent frameworks.
• Working knowledge of core software engineering concepts (Git/GitHub, testing, logging).
• Excellent analytical and problem-solving abilities with attention to detail.

Preferred Skills

• Experience mentoring junior data scientists.
• Background in 10+ years of relevant data science or engineering work.

Key Skills

Education

Any Graduate