Data Analyst II

Job Summary

We are looking for a hands-on Data Scientist & Python Developer with around 5 years of experience in building, deploying, and maintaining machine learning models and data-driven applications.

The role focuses on independent delivery of ML features end to end, working closely with senior data scientists, architects, and product owners.

Key Responsibilities


* Develop, train, and evaluate machine learning models for business and industrial use cases.


* Build Python applications, REST APIs, and data pipelines to operationalize models.


* Develop forecasting, anomaly detection, and predictive analytics models.


* Deploy models using Docker and CI/CD; support model monitoring and retraining.


* Perform data exploration, cleansing, and feature engineering on structured and time-series data.


* Work with product owners and stakeholders to understand requirements and present results.


* Participate in code reviews and support junior team members.

Required Qualifications


* Bachelor's or Master's Engineering degree in Computer Science, Data Science, Engineering, or related field.


* 4-6 years of experience in Data Science, Machine Learning, and Python development, with at least 2 models deployed to production.

Technical Skills


* Programming: Python, SQL; FastAPI or Flask


* ML Libraries: Scikit-learn, XGBoost, Pandas, NumPy; TensorFlow or PyTorch


* Data Engineering: Spark, Airflow (Kafka, Databricks - exposure)


* Cloud: Azure, AWS, or GCP (at least one, hands-on)


* MLOps: Git, Docker, MLflow, CI/CD (Kubernetes - exposure)


* Visualization: Power BI, Tableau, or Plotly

Preferred Experience


* Exposure to Industrial AI, Manufacturing, Energy, or IoT data (sensor / time-series).


* Working knowledge of GenAI, LLMs, RAG, or Agentic AI frameworks.

Ownership & Growth Expectations


* Own ML features/modules end to end with minimal supervision.


* Contribute to design discussions; follow engineering and data science best practices.


* Share knowledge within the team and guide junior members.


* Continuously upskill in emerging AI/ML technologies.

Responsibilities vs.

Competencies Matrix

Responsibility

Key Competencies

ML Model Development

Machine Learning, Statistics, Feature Engineering, Model Evaluation

Python Application Development

Python, REST API Development, Clean Code, Unit Testing

Data Pipeline Engineering

ETL/ELT, SQL, Spark, Airflow (Kafka exposure)

MLOps & Deployment

Docker, CI/CD, MLflow, Model Monitoring

Cloud Solution Development

Hands-on with Azure, AWS, or GCP services

Stakeholder Engagement

Communication, Requirement Understanding, Presenting Insights

Team Collaboration

Peer Reviews, Knowledge Sharing, Guiding Junior Members

Must-Have Skills


* 4-6 years of experience in Data Science and Python development


* Strong Python and SQL; hands-on with Scikit-learn and TensorFlow or PyTorch


* Experience deploying ...