Senior Data Scientist / Lead Data Scientist
Role: Data Scientist
Job Location: Jaipur (Work From Office)
Experience: Experience Required: 4 - 8 yrs
About the Role
As a Senior / Lead Data Scientist at InfoObjects, you will be responsible for designing, developing, and deploying advanced machine learning and statistical models to solve complex business problems. You will work closely with data engineers, business stakeholders, and technology teams to drive data-driven decision-making through predictive analytics, experimentation, and scalable model deployment.
Key Responsibilities
- Design, develop, and deploy end-to-end machine learning models for business use cases such as forecasting, classification, clustering, recommendation systems, and optimization.
- Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights.
- Build predictive models using supervised and unsupervised learning techniques.
- Conduct feature engineering, data preprocessing, and model selection to improve performance and accuracy.
- Develop statistical models and apply hypothesis testing, regression analysis, and time-series forecasting techniques.
- Collaborate with data engineering teams to build scalable data pipelines and production-ready ML systems.
- Monitor model performance, conduct validation, and implement continuous improvement strategies.
- Deploy models into production environments and ensure scalability, reliability, and performance.
- Work closely with business stakeholders to translate requirements into analytical solutions.
- Mentor junior data scientists and promote best practices in data science and model governance.
Must-Have Skills
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
- 4–8 years of hands-on experience in machine learning and predictive analytics.
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, SciPy).
- Experience with ML frameworks such as TensorFlow or PyTorch.
- Strong knowledge of statistical modeling, regression techniques, classification algorithms, clustering, and time-series forecasting.
- Experience with SQL and working with large datasets.
- Hands-on experience with data visualization tools (Power BI, Tableau, Matplotlib, Seaborn).
- Experience working with cloud platforms (AWS / Azure / GCP).
- Strong understanding of ML lifecycle management, model evaluation metrics, and performance tuning.
- Experience in deploying ML models using APIs or containerization (Docker, Kubernetes) is a plus.
- Strong analytical thinking and problem-solving skills.
- Experience mentoring or leading small teams is preferred (for Lead role).