Data Scientist (7–10 Years Experience)
Globalwave Softech Pvt Ltd · Mather, CA · Today
EngineeringContract
About The Role
Globalwave Softech Pvt Ltd is seeking an experienced Data Scientist to design and implement advanced AI/ML models and analytics solutions that drive business insights, automation, and strategic decision-making across functions. In this role, you will own the end-to-end model lifecycle — from business problem scoping to deployment, monitoring, and value realization. You will also help establish reusable AI assets, model governance frameworks, and best practices across the organization. This position requires strong technical expertise combined with business acumen and stakeholder collaboration skills.
Responsibilities
- Translate complex business problems into structured data science solutions
- Perform data preparation, exploratory data analysis (EDA), feature engineering, and hypothesis testing
- Build, validate, and deploy predictive, classification, clustering, and optimization models
- Integrate ML models into enterprise systems using APIs and CI/CD pipelines
- Monitor model performance, detect drift, and manage retraining cycles
- Deliver actionable insights and quantify measurable business impact
- Collaborate with Business, Data Engineering, DevOps, and AI/ML teams
- Mentor junior analysts and contribute to AI/ML best practices and knowledge sharing
- Support model governance, documentation, and reproducibility standards
Technical Skills Required
- Strong proficiency in Python (preferred), R, and SQL
- Solid foundation in Statistics and Machine Learning algorithms
- Experience with Spark, Databricks
- Hands-on exposure to MLflow, Azure ML, AWS SageMaker
- Experience integrating models using APIs and CI/CD pipelines
- Familiarity with Power BI / Tableau for data visualization
- Version control using Git
- Experience working on cloud platforms (Azure preferred)
Good to Have
- Exposure to NLP, Time Series Forecasting, LLMs, or Generative AI
- Experience building scalable production-grade ML systems
- Understanding of MLOps and model governance frameworks