Lead Data Scientist

We’re hiring a
Lead Data Scientist
to join an
End-to-End Optimization
team focused on streamlining complex operational workflows that require a mix of
automation and human review
. In this role, you’ll design and build
production-grade data science solutions
that improve speed, accuracy, and efficiency across decision pipelines—partnering closely with product, engineering, and operations stakeholders to turn ambiguous problems into scalable systems.

What you’ll do

• Own end-to-end data science solutioning : problem framing → data exploration → modeling → deployment → monitoring and iteration
• Build and enhance predictive analytics / ML models in Python to optimize workflow outcomes and throughput
• Create monitoring and performance frameworks (data quality, drift, model performance, KPI health) and translate findings into actionable recommendations
• Break down complex business problems into measurable hypotheses, experiments, and deployable solutions
• Provide technical guidance and mentorship to 2–3 junior data scientists and data engineers
• Collaborate with engineers on productionization (APIs, batch pipelines, orchestration, CI/CD)

What we’re looking for

• Advanced proficiency in Python and strong foundations in predictive modeling / machine learning / statistical modeling
• Proven experience delivering end-to-end, production data science solutions (not just notebooks)
• Cloud experience in GCP, AWS, and/or Azure (GCP preferred)
• Strong software engineering and coding practices (version control, testing, scalable design)
• Experience in operations/logistics/process optimization (supply chain, call centers, workflow efficiency, etc.) is highly valued
• Excellent communication skills; ability to set vision and execute hands-on

Nice to have

• Healthcare experience (optional)
• Familiarity with MLOps patterns (model registries, automated retraining, observability, feature stores)