KSmart Staffing Solutions
Data Scientist - 3 to 8 Years - Bengaluru - WFO - Immediate Joiners Preferrable
Data Scientist (3-8 years) joining a client's Forecasting & Planning Research team in Bengaluru, work-from-office 5 days/week at the customer site. Builds workforce/demand forecasting models with Python, SQL, ML, time series and deep learning, deployed on AWS SageMaker and Docker. Immediate joiners preferred.
- Compensation
- Not disclosed
- Location
- Bengaluru, Karnataka, India
- Work setup
- Onsite
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- Available to join within 15 days (immediate joiners)
- 5+ years of experience as a Data Scientist
- 3+ years hands-on Python and SQL for data analysis and scripting
- Strong expertise in machine learning/statistical modeling and performance tuning
- Proven experience deploying and monitoring models on AWS using SageMaker and Docker
- Solid understanding of demand forecasting and operational capacity planning
- Familiarity with time series models and deep learning for time series forecasting
- Ability to communicate insights to non-technical stakeholders
- Strong documentation and problem-solving skills
- Work from office in Bangalore at customer location, 5 days/week
Nice to have
- Background in forecasting and operations research
Full description
Job Brief
Our client based in Bangalore seeking multiple experienced Data Scientists with a strong foundation in machine learning, Python, SQL, and AWS (SageMaker, Docker), ideally with an operations research background in logistics. You will join a high-performing Forecasting & Planning Research team to develop scalable forecasting models, automate pipelines, and deliver actionable insights that directly impact business outcomes.
Responsibilities
- Immediate Joiners only candidates should be available to join within 15 days
- Work Mode: Work from Office (Bangalore, Customer Location 5 days/week)
- Develop accurate and reliable workforce forecasting models
- Automate model training and deployment using AWS SageMaker and Docker
- Build impact estimation models using time series, probability, and deep learning techniques
- Reduce MAPE across risk functions through model optimization
- Automate data ingestion from Excel to forecasting pipelines
- Improve data quality via rigorous cleaning and transformation processes
- Document code, modeling artifacts, and insights clearly
- Collaborate with cross-functional teams to understand requirements and deliver solutions
- Experiment with cutting-edge forecasting algorithms to enhance modeling infrastructure
Requirements
- 5+ years of experience as a Data Scientist, preferably in forecasting and operations research
- 3+ years of hands-on experience with Python and SQL for data analysis and scripting
- Strong expertise in machine learning/statistical modeling and performance tuning
- Proven experience deploying and monitoring models on AWS using SageMaker and Docker
- Solid understanding of demand forecasting and operational capacity planning
- Familiarity with time series models and deep learning for time series forecasting
- Ability to communicate insights effectively to non-technical stakeholders
- Strong documentation and problem-solving skills