Job Description
Key Responsibilities
- Lead the development and implementation of advanced analytics models and algorithms
- Collaborate with cross-functional teams to understand business needs and formulate data-driven solutions
- Mentor and guide junior data scientists, fostering a collaborative and innovative work environment
- Ensure the delivery of high-quality, actionable insights to support business decision-making
In addition to a competitive salary, leading-edge work, and developing solutions side-by-side with dedicated experts in their fields, Honeywell employees are eligible for a comprehensive benefits package. This package includes employer subsidized Medical, Dental, Vision, and Life Insurance; Short-Term and Long-Term Disability; 401(k) match, Flexible Spending Accounts, Health Savings Accounts, EAP, and Educational Assistance; Parental Leave, Paid Time Off (for vacation, personal business, sick time, and parental leave), and 12 Paid Holidays. For more information,
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates.
YOU MUST HAVE
- Bachelor's degree or Advanced degree in Computer Science, Statistics, Mathematics, or related discipline
- 2+ years of experience within data analysis, statistical modeling, or another related field
- 2+ years' experience with developing and deploying neural network models (deep learning, reinforcement learning, etc.) using PyTorch or TensorFlow
- 1+ years' experience with fine-tuning pre-trained generative AI models (Stable Diffusion, Flux, or LLMs, etc.)
- Highly proficient in general programming languages such as Python and R, and its ecosystem
- Hands-on experience with typical development toolchain such as IDE (VS Code, IntelliJ, etc.), version control system (Git), and Cloud development environment (AWS, etc.)
- Strong project management and organizational abilities
WE VALUE
- Experience in leading and ownership of complex data projects
- Proficiency in working on AI cloud services in Azure, Google, or AWS and MLOps
- Proficiency in creating LLM applications like chatbots
- Strategic thinking and the ability to align data science initiatives with business objectives