Job description
Join NovaQuant Analytics, a leading data science company focused on translating complex data into strategic actions. Based in San Francisco, you will design and deploy scalable ML models that power product decisions and customer insights. You will collaborate with product, ML engineering, and data infrastructure teams to deliver high-impact solutions.
What you will do: build, validate, and deploy end-to-end data science solutions; translate business problems into modeling tasks; communicate results to stakeholders; mentor junior scientists; contribute to data strategy and governance.
Responsibility
- Lead end-to-end data science projects from problem framing to model deployment in production.
- Design, implement, and evaluate ML models addressing business priorities (recommendation, forecasting, anomaly detection).
- Collaborate with product and engineering teams to translate requirements into analytics solutions.
- Develop robust experimentation plans, A/B tests, and measurement of business impact.
- Champion model governance, reproducibility, and code quality; maintain documentation.
- Mentor and coach junior data scientists; contribute to hiring and onboarding.
- Communicate insights and recommendations to non-technical stakeholders with clear data storytelling.
- Prototype novel approaches and stay current with the ML research and cloud tooling.
Qualification
- Masters or PhD in Data Science, Computer Science, Statistics, or a related field; 5+ years of relevant experience.
- Strong proficiency in Python (NumPy, pandas, scikit-learn) and SQL; experience with Spark is a plus.
- Hands-on experience deploying ML models to production (Fargate, Kubernetes, or similar).
- Experience with ML frameworks (TensorFlow, PyTorch); practical knowledge of MLOps tooling.
- Solid experience with cloud platforms (AWS or GCP) and data warehousing (BigQuery, Redshift, Snowflake).
- Excellent problem-solving, communication, and stakeholder management skills.
- Track record of delivering measurable business impact through data-driven decisions.