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Senior Data Scientist - Remote, India
Jobgether
Original Job Summary
Senior Data Scientist - Remote, India
This position is posted by Jobgether on behalf of Velotio Technologies. We are looking for a Senior Data Scientist in India to work on high-impact data engineering and machine learning projects. You will design and deploy scalable data pipelines, develop predictive models, and extract actionable insights from large volumes of customer and campaign data. Collaborate with cross-functional teams, influence product decisions, and contribute to data-driven strategies that enhance customer engagement and business outcomes.
Accountabilities
- Build and maintain scalable data pipelines using AWS services.
- Conduct exploratory analysis with Athena, Redshift, or EMR.
- Design segmentation logic using clustering or rule-based approaches.
- Develop and deploy ML models on Amazon SageMaker.
- Create dashboards using Amazon QuickSight, Tableau, or Power BI.
- Measure campaign performance and recommend optimizations.
- Translate data insights into actionable business recommendations.
Requirements
5+ years in data science or analytics roles with strong proficiency in SQL and Python using libraries like Pandas, Scikit-learn, and XGBoost. Bachelor’s or Master’s in Computer Science, Statistics, Data Science, or related field. Hands-on experience with AWS data stack (S3, Glue, Lambda, Step Functions, Athena, Redshift, SageMaker) and automation tools like Airflow.
Additional Information
Competitive salary, rapid career growth opportunities, and an autonomous work culture with a flat hierarchy. Enjoy a flexible work environment that promotes personal and professional development in an inclusive, diverse, and supportive team culture.
Key Skills/Competency
Senior Data Scientist, AWS, Machine Learning, Data Pipelines, SQL, Python, Data Analysis, Automation, Data Visualization, Cloud Platforms
How to Get Hired at Jobgether
🎯 Tips for Getting Hired
- Customize your resume: Tailor skills and experience to data science.
- Highlight AWS expertise: Emphasize AWS data stack projects.
- Showcase project impact: Detail measurable outcomes.
- Prepare for technical interviews: Review ML algorithms and pipelines.