Data Scientist

About the Role:

We’re looking for a seasoned and inventiveSenior Data Scientistto help design and deploy advanced machine learning systems that drive intelligent features in complex real-world domains.

In this role, you’ll lead the development of end-to-end ML pipelines, shape internal modeling strategies, and accelerate the delivery of AI-powered capabilities to production.

You’ll work cross-functionally with product, engineering, and data teams to prototype, evaluate, and implement solutions grounded in rigorous experimentation and practical impact.

Key Responsibilities:

• ML & AI Development:Research, build, and deploy machine learning models (including generative AI) focused on structured data, NLP, and time series forecasting.
• Model Lifecycle Ownership:Own models from experimentation to deployment, including validation, monitoring, and iteration.
• Generative AI & LLMs:Design and evaluate retrieval-augmented generation (RAG) pipelines, embeddings, and fine-tuning strategies using LLMs.
• Collaboration & Strategy:Partner closely with product and engineering to translate business problems into data science solutions and deliver impactful features.
• Technical Leadership:Contribute to architecture and tooling decisions; mentor junior team members and champion best practices in data science and ML engineering.

Requirements:

• ML Expertise:5+ years of experience in machine learning, data science, or applied AI; strong grasp of supervised/unsupervised learning, deep learning, and probabilistic modeling.
• NLP & LLM Skills:Hands-on experience with NLP pipelines, vector stores, transformer models, and generative AI architectures.
• Production Experience:Demonstrated success in shipping and maintaining ML models in production, including performance monitoring and optimization.
• Strong Programming:Proficiency in Python and ML libraries (e.g., PyTorch, scikit-learn, Hugging Face, etc.); familiarity with MLOps tooling and cloud environments (AWS/GCP/Azure).
• Analytical & Communication Skills:Ability to clearly explain complex ideas, trade-offs, and results to diverse audiences.

Nice to Have:

• Experience with time series forecasting and modeling irregular structured data.
• Background in healthcare, insurance, or other regulated industries.
• Familiarity with vector databases, retrieval systems, or multimodal ML architectures.

THIS POSITION DOES NOT SUPPORT RELOCATION OR SPONSORSHIP