QualificationsMust Have Skills/Project Experience/Certifications

Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related technical field.

4+ years of experience building and deploying machine learning systems in production environments.

Robust software engineering experience with Python and building scalable applications.

Experience designing and implementing production ML pipelines and model lifecycle workflows.

Experience working with distributed data processing frameworks such as PySpark or Spark.

Hands-on experience implementing MLOps practices, including automated model training, CI/CD pipelines, model versioning, and deployment automation.

Experience deploying ML systems on cloud platforms such as AWS, GCP, or Azure.

Familiarity with containerization and orchestration technologies such as Docker and Kubernetes.

Experience working with large-scale datasets and distributed data processing infrastructure.

Experience using ML frameworks such as Scikit-learn, TensorFlow, PyTorch, or similar libraries.

Strong understanding of feature engineering pipelines, model lifecycle management, and model monitoring strategies.





Strong collaboration and communication skills with the ability to work effectively with cross-functional teams including product managers, data scientists, and engineers.

Demonstrated ability to take ownership of complex technical systems and deliver production-ready solutions.

Ability to work effectively across distributed teams and time zones.

Good to Have Skills/Project Experience/Certifications

Experience building and operating real-time or near real-time ML inference systems.

Experience designing or maintaining feature stores or shared ML data infrastructure.

Familiarity with time-series forecasting systems or demand forecasting use cases.

Experience implementing model monitoring, drift detection, and automated retraining strategies.

Experience working with consumer datasets or marketing data in industries such as retail, consumer products, automotive, transportation, or hospitality.

Experience contributing to internal ML platforms, developer tooling, or reusable ML infrastructure.

Education

BE/B.Tech/M.C.A./M.Sc (CS) degree or equivalent from accredited university

Location

Bengaluru/Hyderabad/Pune/Chennai

📌 Data Scientist (AI/ML) - Consultant (Bengaluru)
🏢 Deloitte US-India Offices
📍 Bengaluru