Data Scientist

Hiring: Senior Data Science Engineer

Experience: 4–6 Years

Shift Timings: 1:30 PM – 10:30 PM IST

About the Role

We are looking for a highly skilled Senior Data Science Engineer with 4+ years of experience in building, deploying, and optimizing machine learning solutions. The ideal candidate will have strong expertise in Python, AWS, statistical modeling, and MLOps practices. You will be responsible for the complete machine learning lifecycle, from exploratory data analysis (EDA) and feature engineering to model deployment, monitoring, and optimization.

This role offers an opportunity to work on advanced analytics, Marketing Mix Modeling (MMM), attribution modeling, and cloud-native machine learning solutions while collaborating with cross-functional teams.

Key Responsibilities

End-to-End Machine Learning Development

• Design, develop, and deploy machine learning models using Python and AWS SageMaker.
• Build scalable and production-ready ML pipelines and workflows.
• Perform model evaluation, optimization, and performance monitoring.

Exploratory Data Analysis & Insights

• Conduct deep-dive exploratory data analysis (EDA) to assess data quality and identify actionable business insights.
• Analyze structured and unstructured datasets to support data-driven decision-making.

Data Engineering & Automation

• Develop Python-based solutions for data ingestion, transformation, validation, and deduplication.
• Design and maintain ETL pipelines for processing data from multiple sources.
• Ensure data reliability, quality, and scalability across workflows.

MLOps & Model Management

• Implement model versioning and experiment tracking using MLflow.
• Deploy and manage ML workloads on AWS SageMaker.
• Monitor model performance and ensure reproducibility across environments.

Collaboration & Code Quality

• Participate in GitHub code reviews and maintain coding standards.
• Create modular, reusable, and well-documented code.
• Work closely with Data Scientists, Engineers, and Business stakeholders.

Measurement & Analytics

• Support Marketing Mix Modeling (MMM) and attribution measurement initiatives.
• Apply statistical and Bayesian methodologies to measure media effectiveness and business impact.

Required Skills

Programming & Data Science

• Strong proficiency in Python.
• Expert knowledge of:
• Pandas
• NumPy
• Scikit-learn
• Data visualization experience using:
• Matplotlib
• Seaborn
• Plotly

Data Engineering

• Strong experience in:
• Data ingestion
• Data transformation
• Data validation
• Data quality assessment
• ETL pipeline development

Cloud & Databases

• Hands-on experience with:
• AWS SageMaker
• AWS S3
• AWS DynamoDB
• AWS Lambda
• AWS Glue
• Experience with PostgreSQL databases (AWS/Azure environments).

SQL

• Strong expertise in:
• DDL
• DML
• Query Optimization
• Data Analysis

DevOps & CI/CD

• Experience with:
• GitHub
• Branching Strategies
• Pull Requests
• Code Reviews
• CI/CD Implementations

Testing & Quality Assurance

• Experience writing:
• Unit Tests
• Integration Tests
• Strong focus on code reliability and maintainability.

Statistical Modeling

• Strong foundation in:
• Statistical Modeling
• Machine Learning Algorithms
• Scikit-learn
• Google Meridian

Good to Have

• Experience with Marketing Mix Modeling (MMM).
• Attribution Modeling experience.
• Bayesian Modeling and Google Meridian.
• MLflow for model lifecycle management.
• Docker and containerization.
• MLOps best practices.
• Media effectiveness measurement frameworks.
• Cloud-native machine learning architectures.

Preferred Candidate Profile

• 4–6 years of experience in Data Science and Machine Learning Engineering.
• Strong problem-solving and analytical skills.
• Experience working in Agile environments.
• Ability to independently drive projects from concept to production.
• Excellent communication and stakeholder management skills.

Interested Candidates

Please share your updated CV at Khushboo@Sourcebae.com or WhatsApp at 8827565832.

Stay updated with our latest job opportunities and company news by following us on LinkedIn:

https://www.linkedin.com/company/sourcebae