Data Scientist I

Honeywell Forge’s interview process typically starts with an online aptitude test, followed by a technical interview that probes your understanding of machine learning algorithms, data preprocessing, and coding ability. The final HR round assesses cultural fit and motivation. Candidates should be ready to discuss past projects, solve live coding problems, and articulate how data‑driven solutions can add business value.

Round 1: Online Aptitude & Logical Reasoning → Round 2: Technical Interview (ML concepts, coding, case studies) → Round 3: HR Interview (fit, motivations, culture)

Honeywell Forge promotes a collaborative environment where innovation is encouraged and employees are given autonomy to experiment. The company offers structured learning programs, mentorship, and a balanced work‑life approach, allowing engineers to grow while maintaining personal well‑being.

B.Tech/M.Tech/M.Sc in Computer Science, Statistics, Mathematics, Data Science or related fields; Minimum 60% aggregate (or CGPA 6.5/10); Fresh graduates of 2025‑2027 batches; No active backlogs at the time of joining; Strong foundation in probability, statistics, and linear algebra.

Honeywell Forge, the digital transformation arm of Honeywell International, empowers enterprises across aerospace, building automation, energy, and industrial sectors with cutting‑edge software solutions. Leveraging the power of the Honeywell Forge platform, the company helps customers turn massive streams of data into actionable insights, driving operational efficiency, safety, and sustainability. With a strong heritage of innovation and a global footprint, Honeywell Forge invests heavily in research, AI, and IoT, creating a vibrant ecosystem where engineers, data scientists, and domain experts collaborate to solve some of the world’s most complex challenges. The culture emphasizes continuous learning, cross‑functional teamwork, and a commitment to delivering measurable business value. As a Data Scientist I, you will be at the forefront of this data‑driven journey. Reporting to senior data scientists, you will apply statistical modeling, machine learning, and advanced analytics to real‑world problems ranging from predictive maintenance of industrial equipment to demand forecasting for energy consumption. You will work closely with product managers, software engineers, and domain specialists to translate business requirements into robust analytical solutions, prototype models, and production‑ready pipelines. This role offers a unique blend of technical depth and business impact, giving a fresh graduate the chance to see their models influence decisions that affect millions of users worldwide. Key responsibilities include: 1. Design, develop, and validate machine‑learning models that address specific business problems. 2. Perform end‑to‑end data pipelines: data ingestion, cleaning, feature engineering, model training, and deployment. 3. Conduct exploratory data analysis to uncover hidden patterns and insights. 4. Collaborate with cross‑functional teams to integrate models into Honeywell Forge applications. 5. Document methodology, code, and results for reproducibility and knowledge sharing. 6. Participate in code reviews and adopt best practices for version control and testing. 7. Stay updated with the latest research in AI/ML and propose innovative approaches. 8. Mentor junior interns or peers on analytical techniques and tools. 9. Contribute to the strategic roadmap of the Data Science team by identifying new use‑cases. 10. Communicate findings to non‑technical stakeholders through visualizations and clear narratives. The tech stack typically includes Python (pandas, scikit‑learn, TensorFlow/PyTorch), SQL, cloud platforms (AWS/GCP), containerization (Docker), and CI/CD pipelines. Growth paths lead to Senior Data Scientist, Lead Data Scientist, and eventually managerial or specialist roles within Honeywell’s AI/Analytics divisions. Joining Honeywell Forge offers exposure to large‑scale industrial data, mentorship from seasoned professionals, and a clear trajectory for career advancement in a globally recognized organization.