Data ScientistFull-time

About the Role

We are looking for a highly motivated Junior Data Scientist to support the end-to-end analytics lifecycle—from data exploration to model development and insights delivery. The ideal candidate will help uncover patterns hidden in large datasets, support data-driven decision-making, and contribute to building scalable statistical and machine learning solutions.

You will be responsible for data analysis, reporting, model development, data pipeline support, and stakeholder communication. This role also provides opportunities to work on production-grade analytics systems and real business use cases.

Key Responsibilities

Data Analysis & Exploration

• Collect, clean, and analyze large structured and unstructured datasets.
• Perform exploratory data analysis (EDA) to identify trends, anomalies, and insights.
• Create meaningful data visualizations and dashboards for decision-making.

Model Development & Statistical Analysis

• Develop statistical models, machine learning algorithms, classification and regression models.
• Perform feature extraction, selection, and engineering.
• Optimize and validate models for accuracy, interpretability, and reliability.

Model Deployment Support

• Build reusable and maintainable code modules to support moving models into production.
• Work with engineering teams to integrate ML models into existing systems and workflows.

Data Engineering Support

• Support development and maintenance of data pipelines, ETL processes, and data infrastructure.
• Work closely with data engineers to ensure high data quality and availability.

Insight Generation & Reporting

• Translate analytical findings into clear, actionable insights for business stakeholders.
• Present reports, dashboards, and presentations in a user-friendly manner.
• Collaborate with cross-functional teams to embed analytics in business processes.

Continuous Learning & Innovation

• Stay updated with the latest trends in data science, ML/AI, cloud analytics, and automation.
• Contribute to innovative solutions and process improvements across the analytics team.

Knowledge & Skills Required

Technical Skills

• Strong mathematical, analytical, and logical reasoning skills.
• Proficiency in Python or R (preferred: pandas, NumPy, scikit-learn, TensorFlow, PyTorch).
• Good understanding of SQL for data querying and manipulation.
• Hands-on experience with data visualization tools (Matplotlib, Seaborn, Power BI, Tableau, etc.).
• Strong understanding of statistics, probability, regression, classification, and model evaluation techniques.
• Exposure to cloud platforms such as AWS, Azure, or Google Cloud.
• Understanding of data pipelines and basic ETL concepts.

Soft Skills

• Ability to communicate complex analytical concepts in simple terms.
• Strong documentation and presentation skills.
• Ability to collaborate with both technical and non-technical teams.
• Proactive, curious, and willing to learn new techniques quickly.

Education Requirements

• Bachelor’s degree in Data Science, Computer Science, Mathematics, Statistics, Engineering or related field with minimum 60% aggregate.
• Post-graduate degree in Data Science or Analytics is preferred (minimum 60% aggregate).
• Certifications in Machine Learning, AI, Big Data, Cloud Analytics are an added advantage.