About the Role
We are looking for an experienced and execution-driven Senior Data Scientist to build, deploy, and optimize machine learning solutions at scale. This is a hands-on role requiring expertise across machine learning, big data technologies, cloud platforms, and production-grade data systems.
You will work on end-to-end data science projects—from experimentation and feature engineering to model deployment and optimization—while collaborating with engineering teams to deliver high-impact business outcomes.
Key Responsibilities
- Design, develop, and deploy scalable machine learning models into production environments.
- Build predictive and advanced analytics solutions using Python, SQL, Pandas, Scikit-learn, TensorFlow, and PyTorch.
- Process and analyze large-scale datasets using Apache Spark, Databricks, and Hadoop.
- Develop automated workflows and pipelines using Airflow and AWS EMR.
- Collaborate with engineering teams to integrate ML models into cloud-based applications.
- Perform feature engineering, model training, evaluation, validation, and deployment.
- Optimize SQL queries, storage systems, and data pipelines for performance and scalability.
- Monitor model performance and drive continuous improvements.
- Independently own projects and deliver business-focused outcomes.
- Stay updated with the latest developments in machine learning, big data, and cloud technologies.
Required Skills
- 5+ years of experience in Data Science, Machine Learning, or Applied AI.
- Strong proficiency in Python and SQL.
- Hands-on experience with Scikit-learn, TensorFlow, PyTorch, and Pandas.
- Experience deploying machine learning models into production systems.
- Strong expertise in Apache Spark, Hadoop, and distributed computing.
- Hands-on experience with Databricks, Airflow, and AWS EMR.
- Good understanding of AWS services such as S3, EC2, Lambda, SageMaker, and related cloud tools.
- Experience building scalable data pipelines and optimizing query performance.
- Strong analytical, problem-solving, and communication skills.
Preferred Experience
- Experience in AdTech, recommendation systems, personalization, marketing analytics, or large-scale data platforms.
- Familiarity with MLOps, model monitoring, and cloud-native deployments.
- Exposure to Kubernetes or containerized environments is a plus.
Why Join?
- Work on large-scale machine learning and data science problems.
- Collaborate with high-performing engineering and product teams.
- Build AI-driven solutions used by global customers.
- Opportunity to work with modern ML, big data, and cloud technologies.
Pay: ₹5,000,000.00 - ₹6,000,000.00 per year
Work Location: Remote
