About the role
- Develop and maintain machine learning models and forecasting solutions.
- Perform data cleaning, preprocessing, and feature engineering.
- Build and optimize data pipelines using Python and SQL.
- Analyze large datasets to identify trends and business insights.
- Support model deployment, testing, and performance monitoring.
- Create dashboards, reports, and data visualizations.
- Assist in developing automated prediction and retraining workflows.
- Collaborate with cross-functional teams on analytics projects.
- Document model development activities and technical processes.
- Stay updated with emerging trends in Data Science and AI.
RequirementsRequirements
- 1-3 years of experience in Data Science, Machine Learning, or Analytics.
- Strong proficiency in Python and SQL.
- Good understanding of Machine Learning, Forecasting, Regression, Classification, and Clustering.
- Experience with data analysis, feature engineering, and model development.
- Exposure to Azure Cloud, Azure ML, Snowflake, or similar platforms.
- Familiarity with Git, version control, and ML deployment concepts.
- Strong analytical, problem-solving, and communication skills.
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related field.
- Azure Machine Learning.
- Power BI or Tableau.
- Time Series Forecasting.
- MLOps fundamentals.
- Internship/project experience in AI/ML.
- Experience working with cloud-based data platforms.
BenefitsBenefits & Perks
Financial Benefits
- Provident Fund (PF)
- Competitive Salary Package
- Annual Performance Reviews
- Leave Encashment Benefits
- Medical Insurance Coverage
- Insurance for Employee & Family Dependents
- 5-Days Working Week
- Hybrid Working Model
- Paid Annual Leave
- Sick Leave & Casual Leave
- Company Holidays
- Maternity Leave
- Paternity Leave
- Mentorship from Senior Data Scientists
- Exposure to Global Projects
- Continuous Learning Opportunities
- Career Growth Path in Data & AI
- Friendly & Inclusive Work Environment
- Collaborative Team Culture
- Employee Engagement Programs
- Team Outings & Celebrations
- Recognition & Rewards