Data Scientist

Honeywell’s interview process typically starts with a timed online assessment focusing on quantitative aptitude, coding, and basic ML concepts. This is followed by a technical interview where candidates discuss past projects, solve case‑based problems, and answer deep‑dive questions on algorithms and statistics. The final HR round assesses cultural fit, communication skills, and career aspirations. Overall difficulty is moderate to high, and thorough preparation of core concepts and practical project experience is key.

Honeywell promotes a collaborative and inclusive work culture where innovation is encouraged and employees are given autonomy to experiment. The company offers structured learning pathways, regular hackathons, and a balanced work‑life environment with flexible timings.

Bachelor's or Master's degree in Computer Science, Information Technology, Electronics & Communication, Statistics, Mathematics or related fields; minimum 60% aggregate (or CGPA 6.0/10); final year students of 2025‑2027 batches eligible; no active backlogs at the time of joining; strong academic record in quantitative subjects.

Round 1: Online aptitude & coding test → Round 2: Technical interview (ML concepts, case studies) → Round 3: HR interview (fitment, motivations)

Honeywell is a global technology and manufacturing leader with a presence in more than 70 countries. In India, the company operates across aerospace, building technologies, performance materials, and safety & productivity solutions, delivering innovative products that improve efficiency and sustainability. With a strong focus on research and development, Honeywell invests heavily in cutting‑edge technologies such as artificial intelligence, IoT, and advanced analytics, making it an attractive destination for fresh engineering talent looking to work on real‑world impact. The Data Scientist role at Honeywell Bengaluru is designed for fresh graduates who are eager to translate data into actionable business insights. As a member of the Data Science team, you will collaborate with product managers, engineers, and business stakeholders to solve complex problems ranging from predictive maintenance of industrial equipment to demand forecasting for smart building solutions. The position offers a blend of hands‑on modeling, algorithm development, and end‑to‑end project ownership, providing a solid foundation for a long‑term career in analytics. **Key Responsibilities** 1. Design, develop, and deploy machine‑learning models that address specific business challenges. 2. Perform exploratory data analysis, feature engineering, and statistical testing on large, heterogeneous datasets. 3. Manage end‑to‑end data science projects, ensuring alignment with business objectives and timely delivery of insights. 4. Create clear visualizations and dashboards to communicate findings to non‑technical stakeholders. 5. Collaborate with software engineers to integrate models into production pipelines. 6. Mentor junior data scientists and interns, fostering a culture of continuous learning. 7. Contribute to the strategic roadmap of the Data Science team by proposing new use‑cases and research directions. 8. Stay updated with the latest advancements in AI/ML and evaluate their applicability to Honeywell’s product portfolio. 9. Ensure data quality, governance, and compliance throughout the modeling lifecycle. 10. Document methodologies, code, and results for reproducibility and knowledge sharing. **Tech Stack**: Python, R, SQL, Spark, TensorFlow/PyTorch, Scikit‑learn, Tableau/PowerBI, AWS/GCP, Docker, Git. **Growth Path**: Starting as an Associate Data Scientist, high performers can progress to Senior Data Scientist, Lead Analyst, and eventually to roles such as Data Science Manager or Head of Analytics, with opportunities to move across Honeywell’s diverse business units. **Why Join Honeywell?** The company offers a vibrant, innovation‑driven environment, competitive compensation (10‑12 LPA), robust learning programs, and exposure to industry‑leading projects. Freshers get mentorship from seasoned professionals, access to global resources, and a clear career trajectory, making Honeywell an excellent launchpad for a data‑centric career.