Honeywell is looking for a Data Scientist with strong analytical and machine learning skills to focus on hands‑on analysis, model building, and deployment support. You will work closely with senior data scientists, engineers, and product teams to convert business problems into data science use cases and build scalable ML solutions.
What You'll Do
- Perform exploratory data analysis (EDA) on structured and semi‑structured data
- Clean, preprocess, and transform large datasets
- Create clear visualizations and insights for stakeholders
- Write efficient and readable SQL queries for analysis and reporting
- Work on NLP tasks such as text classification, similarity, and entity extraction
- Use pre‑trained models from Hugging Face or cloud APIs
- Assist in building LLM‑based applications (prompt engineering, simple RAG pipelines)
- Evaluate outputs for quality, relevance, and bias
- Consume data from data warehouses and data lakes
- Build or modify batch data pipelines using Spark or Python
- Assist with workflow orchestration using Airflow or Prefect
- Understand basic streaming concepts (Kafka exposure is a plus)
- Package models for deployment with guidance from senior team members
- Support model deployment using REST APIs like FastAPI
- Track experiments, metrics, and models using tools like MLflow
- Monitor basic model performance and data quality post‑deployment
- Work closely with product managers, analysts, and engineers
- Clearly communicate findings and recommendations
- Participate in code reviews and team discussions
- Continuously learn and apply new tools and techniques
What We're Looking For
- 3–6 years of relevant industry experience
- Strong proficiency in Python (pandas, numpy, scikit‑learn)
- Good knowledge of SQL (joins, aggregations, subqueries)
- Solid understanding of Statistics & probability
- Solid understanding of Linear regression and classification models
- Experience with machine learning libraries scikit‑learn
- Experience with XGBoost or LightGBM (preferred)
- Experience with Jupyter notebooks
- Familiarity with Spark or PySpark (hands‑on or project experience)
- Basic experience with MLflow or similar experiment tracking tools
- Version control using Git
- Working knowledge of at least one cloud platform: AWS, Azure, or GCP
- Experience querying data from Snowflake, BigQuery, Redshift, or similar
- Basic understanding of data lakes and warehouses
- Hands‑on experience with Linear Regression
- Hands‑on experience with Logistic Regression
- Hands‑on experience with Decision Trees
- Hands‑on experience with Random Forest
- Hands‑on experience with Hierarchical Clustering
Nice to Have
- Exposure to PyTorch or TensorFlow
- Experience with NLP or GenAI projects
- Familiarity with Docker
- Understanding of basic data engineering concepts
- Experience working in agile teams
Technical Stack
- Python, pandas, numpy, scikit‑learn, SQL, XGBoost, LightGBM
- Jupyter notebooks, Spark, PySpark, MLflow, Git
- AWS, Azure, GCP, Snowflake, BigQuery, Redshift
- Hugging Face, REST APIs, FastAPI, Airflow, Prefect, Kafka
- PyTorch, TensorFlow, Docker
Work Mode
This is a hybrid position based in Bangalore, India.
Honeywell is an equal opportunity employer.
