Job Description
We are looking for a Data Scientist who can build data-driven solutions, develop machine learning models, and support analytics initiatives. The role requires strong expertise in data analysis, data pipelines, and statistical modeling, with exposure to AI and generative AI technologies as part of modern data solutions.
Key Responsibilities
Data Engineering & Data Pipelines
- Design, develop, and maintain automated data pipelines using Python and ETL tools.
- Collect, clean, and transform data from multiple sources including APIs, databases, and web scraping.
- Manage and optimize SQL and NoSQL databases to ensure reliable and high-quality datasets.
- Implement data validation, monitoring, and documentation for datasets.
Data Science & Machine Learning
- Develop and deploy machine learning models for regression, classification, and clustering.
- Perform exploratory data analysis (EDA) to identify trends and insights.
- Apply statistical techniques and model evaluation methods to improve model performance.
- Support experimentation and data-driven decision-making.
AI & Advanced Analytics (Supporting Role)
- Apply AI and NLP techniques to enhance data-driven products and analytics solutions.
- Work with pre-trained models and frameworks to build intelligent features and insights.
- Support basic use cases involving generative AI, such as information retrieval, text analysis, or automation.
Analytics & Visualization
- Build dashboards and reports using BI tools such as Tableau, Power BI, or Looker Studio.
- Translate technical findings into clear insights for business stakeholders.
Collaboration & Delivery
- Work closely with engineering, product, and business teams to deliver data solutions.
- Contribute to backend logic and API integrations when required.
- Follow best practices in version control, documentation, and agile development.
Required Skills & Qualifications
Core Skills
- Strong proficiency in Python and data science libraries (Pandas, NumPy, Scikit-learn).
- Solid understanding of machine learning concepts and statistical analysis.
- Experience with SQL and data modeling; exposure to NoSQL databases is a plus.
- Experience with ETL pipelines, data integration, and data warehousing concepts.
- Experience with data visualization tools (Tableau, Power BI, etc.).
AI Exposure (Preferred, Not Mandatory)
- Exposure to deep learning, or generative AI concepts and tools.
- Familiarity with frameworks such as TensorFlow, PyTorch, or Lang Chain is an advantage.
Tools & Platforms
- Familiarity with cloud platforms (GCP, AWS, or Azure).
- Experience with Docker, Linux, APIs, and Git is a plus.
Education & Experience
- Bachelor’s degree in computer science, Data Science, Engineering, or related fields.
- Minimum 2 years of experience in data science, analytics, or related roles.
Soft Skills
- Strong analytical and problem-solving skills.
- Good communication and stakeholder management abilities.
- Ability to work in a fast-paced environment and learn new technologies quickly.