Data Scientist

As a part-time Data Scientist with over 4 years of experience, you will be responsible for building the Machine Learning foundation for a high-velocity US-focused startup. The position offers approximately 3 months of work initially, with the potential for a full-time role requiring 12 hours per week. It is important to note that Data Analytics is distinguished from Data Science. Inveno, a New York City-based startup, aims to automate the manual resource planning processes that occur daily at warehouses across the United States. The current problem being addressed is the reliance of 75% of US warehouses on manual shift planning, leading to inefficiencies amounting to over $1 million per warehouse annually. By utilizing operational data and developing custom AI and optimization models, Inveno seeks to assist warehouse managers in planning with precision, speed, and scalability. The founding team behind Inveno consists of a warehouse operations expert with 8 years of experience, a CEO with a successful track record of building and exiting companies, and a CTO experienced in scaling engineering and systems across various ventures globally. The company has made significant progress, with the V1 product set to go live with the first client in 2 months. Inveno has also secured a paid contract with a global multi-brand conglomerate and has a promising pipeline with some of the largest retailers in the US. As a Data Scientist in this role, you will be responsible for leading the development of the optimizer, building machine learning models, collaborating on the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing core optimization engines, creating supervised learning models, designing workflows, and setting up model versioning and deployment pipelines. Qualifications and skills required for this position include experience in designing and deploying constraint-based optimization models, advanced Python skills, a strong foundation in supervised machine learning, the ability to translate complex operational problems into solvable models, and a degree in Computer Science, Operations Research, Statistics, or a related quantitative field.,