Senior Data Scientist

Who We Are

At Bennett Data Science, we've been pioneering the use of predictive analytics and data science for over a decade for some of the biggest brands and retailers. We're at the top of our field because we focus on delivering actionable AI for our clients. Our deep experience and product-first attitude set us apart from other groups and gets us the business results our clients want.

Why You Should Work With Us

You'll be exposed to a wide range of clients who are at the cutting edge of innovation in their field and get to work on fascinating problems, supporting real products, with real data. We help lots of companies, from some of the largest companies in the world to small startups in Silicon Valley who are building the next big thing.

Expert Mentorship: Direct guidance from senior staff with 20+ years of applied ML experience

Competitive Compensation: Market-rate pay with performance upside

Fully Remote: Work from any location of your choice, on a flexible schedule

Real Impact: Your models go into production and serve real users

The Role

As a Senior Data Scientist, you will lead the design, development, and deployment of production machine learning models. You will work directly with stakeholders to understand their business problems, translate them into data science solutions, and deliver measurable impact. You will also mentor junior team members and drive technical excellence across engagements.

You'll own projects end-to-end, from exploratory analysis and model development through deployment, monitoring, and iteration alongside senior data engineers. This is a hands-on, individual contributor role at a senior level. Client-facing communication is part of the job.

Requirements

A successful candidate has 5+ years of experience in applied data science and machine learning, a strong statistical foundation, and demonstrates the following:

• Production ML experience: building, deploying, and maintaining models that serve real users at scale
• Strong Python skills including scikit-learn, pandas, NumPy, and at least one deep learning framework (PyTorch or TensorFlow)
• Proven experience building predictive scoring, classification, or ranking models deployed to production at scale
• Proficiency in SQL and comfort working with large-scale data warehouses (Redshift, Snowflake, BigQuery)
• Experience deploying RAG-based chat bots, including  how to reduce hallucinations and a strong understanding of the tradeoffs across various approaches
• Solid statistical foundation: hypothesis testing, distributions, probability, experimental design
• Experience communicating findings and model recommendations to non-technical stakeholders
• Comfort working independently across multiple projects simultaneously
• English proficiency at B2 or above (written and spoken)

Nice to Have

• Experience applying LLMs or transformer-based NLP for structured text classification, information extraction, or embedding-based retrieval
• Geospatial feature engineering — location-based statistics, spatial indexing, or OpenSearch for proximity scoring
• Experience with Vision-Language Models (VLMs) or satellite/aerial imagery analysis
• Familiarity with MLOps tooling — experiment tracking (MLflow, W&B), model registries, CI/CD for ML
• Experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI)
• Exposure to utilities, energy, infrastructure, or enterprise SaaS domains
• Experience fine-tuning or adapting pre-trained models (LoRA, PEFT, or full fine-tune)

Role Expectations

• This is a production role. We build systems that run in the real world