Senior Data Scientist - Analytics & MLOps
First seen by Alion on Oct 5, 2026.
Job Summary:
We are looking for a technically strong Senior Analytics Engineer / Data Scientist to own both sides of a modern analytics and ML platform: Designing and rigorously reviewing SQL-based data pipelines and business insight logic on Google BigQuery, and owning the end-to-end MLOps lifecycle for models running in production on GCP.
This role blends hands-on engineering with technical review responsibility.
Responsibilities:
- Design and implement BigQuery SQL procedures, views, and table functions for business insight generation.
- Analyze and optimize BigQuery query for cost and performance and enforce shared architectural conventions.
- Own the end-to-end MLOps lifecycle - model packaging, versioning, cloud deployment, monitoring, and automated retraining pipelines on GCP using Vertex AI, MLflow, or Kubeflow.
- Design and maintain CI/CD pipelines for ML models, ensuring reliable, repeatable deployments.
- Set up model monitoring to track prediction drift, data drift, and performance degradation.
- Conduct evidence-based code reviews - validating logic against live production data.
- Define and enforce data quality governance standards across all ML feature pipelines.
- Validate model outputs and analytical findings for statistical soundness.
- Collaborate with data engineers, domain experts, and product managers to translate ambiguous requirements into precise designs.
Mandatory Skills:
- Strong hands-on experience with BigQuery and advanced SQL.
- Deep ownership of MLOps - CI/CD for ML, model versioning, deployment automation, and drift monitoring on GCP or AWS.
- Strong Python skills for production-grade ML code.
- Demonstrated ability to review code by verifying against real data.
- Hands-on experience implementing data quality governance.
- Proven ability to perform insights validation.
- Strong grounding in statistical modeling.
- Excellent written communication for documenting decisions.
- Experience with version control (Git) and agile workflows.
Education & Experience:
- B.Tech / M.Tech.
- 5 to 8 years of overall experience, including 3+ years of hands-on BigQuery/SQL-at-scale work and meaningful exposure to production ML systems.
Skills
Data Science, Data Analytics, Machine Learning, Big Data, Predictive Analytics, Data Scientist, SQL, Data Modeling, Python