Machine Learning Engineer Data Scientist

With a startup spirit and 130,000+ curious and courageous minds, we have the expertise to go deep with the world's biggest brands and we have fun doing it. Now, we're calling all you rule-breakers and risk-takers who see the world differently and are bold enough to reinvent it. Come, transform with us.
Transformation happens here. Come, be a part of our exciting journey!

Are you the one we are looking for?

Inviting applications for the role of Machine Learning Engineer / Data Scientist (Databricks & Snowflake)
Role Overview
We are seeking a highly motivated Machine Learning Engineer / Data Scientist with hands-on experience in Databricks, Snowflake, MLflow, and Unity Catalog, along with strong Python expertise.
This role bridges advanced analytics and production ML engineering. The ideal candidate can build robust models, operationalize them using modern MLOps practices, and design scalable data pipelines within cloud-native environments. Key Responsibilities
=9 Machine Learning & Advanced Analytics

• Develop, train, validate, and deploy machine learning models for predictive and analytical use cases
• Perform exploratory data analysis (EDA) and feature engineering
• Apply statistical modeling, supervised/unsupervised learning, and optimization techniques
• Evaluate models using robust validation frameworks
• Communicate insights clearly to technical and business stakeholders

=9 ML Engineering & MLOps

• Productionize ML models using MLflow for experiment tracking, model registry, and lifecycle management
• Implement CI/CD pipelines for ML workflows
• Monitor model performance and manage version control
• Ensure reproducibility and governance of ML assets
• Manage feature pipelines and model retraining strategies

=9 Databricks & Distributed Processing

• Build scalable data pipelines using Databricks (Spark)
• Optimize distributed workloads for performance and cost efficiency
• Implement notebook-based and production-grade job workflows
• Leverage Unity Catalog for governance, lineage, and secure data/model access control

=9 Data Warehousing & Snowflake

• Design and optimize data models in Snowflake
• Write advanced SQL queries for transformation and analytics
• Integrate Snowflake with Databricks for seamless data workflows
• Support ELT/ETL design and performance tuning

Required Qualifications
Technical Skills

• Strong programming skills in Python (pandas, NumPy, scikit-learn, etc.)
• Hands-on experience with Databricks (Spark, notebooks, jobs)
• Experience with Snowflake
• Working knowledge of MLflow
• Experience implementing governance using Unity Catalog
• Strong SQL proficiency
• Understanding of distributed computing concepts

Preferred Qualifications

• Experience deploying ML models in cloud environments (AWS/Azure/GCP)
• Familiarity with REST APIs and model serving
• Experience with deep learning frameworks (PyTorch/TensorFlow)
• Exposure to data quality frameworks
• Knowledge of feature stores and real-time inference pipelines

Soft Skills

• Strong problem-solving and analytical skills
• Ability to translate business requirements into technical solutions
• Strong communication and documentation capabilities
• Ability to work in cross-functional agile teams

Why Join Us

• Lead the next generation of Risk Analytics & AI-enabled Risk Solutions for global financial institutions.
• Work at the intersection of risk, data, technology, and regulation, shaping the future of risk management.
• Collaborate with global experts, alliances, and innovation labs to build cutting-edge solutions.
• Opportunity to make an impact at scale while growing a high-performing, future-ready team.