Job description
NovaData Technologies is a fast-growing data science company focused on building AI-powered products for enterprise clients. We are looking for a Senior Data Scientist to design and deploy models that drive measurable business outcomes.
You will partner with product, engineering, and marketing teams to translate ambiguous problems into actionable ML solutions, iterate on models with robust evaluation, and deploy scalable systems in production.
We value curiosity, collaboration, and a bias toward action. If you thrive in a fast-paced environment and want to shape the next generation of data-driven products, we want to hear from you.
Responsibility
- Lead end-to-end ML projects from problem framing to deployment, monitoring, and iteration.
- Collaborate with cross-functional teams to translate business requirements into analytical experiments and ML models.
- Design, implement, and optimize predictive models (classification, regression, time-series) with scalable pipelines.
- Ensure model robustness with rigorous validation, bias testing, and fairness considerations.
- Champion MLOps practices including versioning, experiments tracking, and automated retraining.
- Communicate insights and results to non-technical stakeholders through clear visualizations and storytelling.
- Mentor junior data scientists and contribute to a culture of data-driven decision making.
- Stay current with industry trends, contribute to open-source initiatives, and document best practices.
Qualification
- PhD or Master’s degree in Computer Science, Statistics, Mathematics, or a related field; or equivalent practical experience.
- 5+ years of hands-on data science experience with production ML models.
- Proficiency in Python (pandas, scikit-learn, NumPy) and at least one deep learning framework (TensorFlow, PyTorch).
- Strong SQL skills and experience with data warehousing and ETL pipelines (Snowflake, Redshift, BigQuery).
- Experience deploying ML models in cloud environments (AWS, GCP, or Azure) and using MLOps tools.
- Solid understanding of statistics, experimental design, A/B testing, and causal inference.
- Excellent communication skills and ability to explain complex concepts to non-technical audiences.