Senior Data Scientist
About Us
Hexight is a well funded start-up currently in the seed stage, with an operational product and paying clients, expecting to grow rapidly in the coming years. Hexight specializes in software development for supply chain management, offering solutions that leverage advanced planning and forecasting techniques to help businesses make smarter and faster decisions amidst uncertainty. Our expertise includes demand forecasting, experiment-driven planning, and probabilistic planning/forecasting.
Key Responsibilities
As a Senior Data Scientist, you will be instrumental in developing and deploying advanced data-driven solutions. Your responsibilities will include:
- Designing, developing, and implementing production-grade machine learning models and probabilistic time series analysis models.
- Analyzing complex datasets to extract actionable insights.
- Developing and implementing algorithmic solutions to optimization problems.
- Collaborating with cross-functional teams to integrate ML solutions into the product.
- Staying up to date on the latest advancements in data science and machine learning, and applying them to our business challenges
Requirements
We are looking for a highly skilled and motivated individual who meets the following qualifications:
- Experience: A Bachelor's degree in Computer Science (CS), Electrical Engineering (EE), or a related quantitative field with 5+ years of relevant industry experience, or a Master's degree/Ph.D. with 4+ years of experience.
- Proven experience solving data science problems using tabular data.
- Strong expertise in Python programming and its core data science libraries (e.g., pandas, scikit-learn, NumPy).
- Experience working as part of a team.
- Ability to learn quickly, including cutting edge technologies and research.
Advantages
Candidates with the following experience will be highly regarded:
- Proficiency in time series analysis.
- Experience with optimization problems.
- Strong foundation in statistical modeling and probability theory.
- Experience with MLOps practices and tools.
- Experience with cloud computing infrastructure.
- Experience with probabilistic forecasting.
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