Job description
Join TechNova Analytics, a premier data science partner empowering leading enterprises to unlock value from data. We are seeking a highly capable Data Scientist to translate complex datasets into actionable insights, influence product strategy, and deliver measurable business impact. This role blends advanced machine learning, statistics, and experimentation to solve real-world problems in commerce, healthcare, and energy sectors. This position is based in Seattle with hybrid work flexibility.
As part of a collaborative, high-performance team, you will work across product, engineering, and business to design, implement, and monitor data-driven solutions that scale.
Responsibility
- Lead end-to-end data science projects from problem framing to model deployment and monitoring in production.
- Translate business questions into analytic strategies, define success metrics, and communicate findings to non-technical stakeholders.
- Develop robust predictive models (classification, regression, time-series, NLP) using Python, SQL, and modern ML frameworks.
- Experiment design and statistical analysis to drive A/B testing and causal inference for product decisions.
- Collaborate with data engineers to ensure reliable data pipelines, feature stores, and scalable model serving.
- Interpret model outputs, produce clear visualizations, and deliver insights through dashboards and reports.
- Mentor junior data scientists, contribute to best practices in MLOps, model validation, and governance.
Qualification
- Master's or PhD in Computer Science, Statistics, Mathematics, or a related field; or equivalent industry experience.
- 5+ years of hands-on data science experience with a strong track record of delivering business impact.
- Proficiency in Python (pandas, scikit-learn) and SQL; experience with ML frameworks such as TensorFlow or PyTorch.
- Solid understanding of statistics, experimental design, and causal inference techniques.
- Experience deploying models to production and working with MLOps concepts (model versioning, monitoring, retraining).
- Strong communication and collaboration skills; ability to translate complex findings into actionable recommendations.
- Experience with cloud platforms (AWS or GCP), data visualization tools, and large-scale data processing.