Data Science Intern
xynvia- Posted an hour ago
- Be among the first 10 applicants
Job Description
Open role / Internship
InternshipIntermediate foundationKozhikode · Hybrid
Data Science InternExtract actionable intelligence from complex datasets, prototype machine learning models, and build reproducible data pipelines supporting Xynvia's healthcare and enterprise AI systems.
Apply for this role 01Intermediate capability 02Real product work 03Hybrid collaborationRole standard
Ready to contribute. Still ready to learn.
At least one end-to-end data science project or a credible portfolio demonstrating exploratory data analysis (EDA), statistical modelling, feature engineering, and model evaluation.
What matters most
Show us how you think, what you have built or learned, and how you improve work after feedback.
Responsibilities
What you will own.
- 01Clean, explore, and preprocess structured and unstructured data to extract meaningful patterns and baseline metrics.
- 02Develop, evaluate, and benchmark machine learning and statistical models using sound validation techniques.
- 03Build and maintain reproducible data pipelines, ETL scripts, and analytical workflows for real-world datasets.
- 04Collaborate with engineering teams to package and serve model prototypes via lightweight APIs (FastAPI / Flask).
- 05Document analytical methodologies, dataset assumptions, validation results, and experiment findings with clarity.
Intermediate skills
What you should bring.
- Proficiency in Python and core data libraries (Pandas, NumPy, Scikit-Learn)
- Strong foundation in statistics, hypothesis testing, probability, and exploratory data analysis
- Intermediate SQL for querying, aggregating, and structuring relational data
- Working knowledge of machine learning algorithms (regression, classification, clustering, ensemble methods)
- Familiarity with data visualization tools (Matplotlib, Seaborn, Plotly) and version control (Git)
Useful, not required: Experience with PyTorch, TensorFlow, NLP / LLM concepts, computer vision basics, vector databases, FastAPI, Docker, or PostgreSQL is useful.
Early outcomes
What good progress looks like.
01A validated, reproducible data pipeline or predictive model benchmarked against defined performance metrics
02A lightweight inference API or analytical dashboard presenting model predictions and business insights
03Clear experiment documentation, error analysis, and actionable recommendations for the production team
Hiring path
Clear and role-relevant.
01
Application review
Resume, portfolio and evidence of practical ability.
02
Working conversation
Your thinking, interests and relevant experience.
03
Practical review
A focused task or work sample when useful for the role.
04
Final alignment
Scope, expectations, location and next-step clarity.
The sequence may vary by role. Xynvia does not ask candidates to complete unpaid production work.
Interested / apply directly
Bring the work that shows your thinking.
Attach your resume and include a portfolio, GitHub, case study or relevant work sample where available.
Apply for Data Science InternMore Info
Key Skills
Plotly
Ensemble methods
Scikit-Learn

