Part-time Data Scientist

As a part-time Data Scientist with more than 4 years of experience, you will have the opportunity to build the machine learning foundation for a high-velocity US-focused startup. The position involves approximately 3 months of work initially, with the potential for full-time engagement (12 hours per week). Inveno, a New York City-based startup, is dedicated to automating the manual resource planning processes that occur daily in US warehouses. The primary problem being addressed is the prevalent manual shift planning in 75% of US warehouses, leading to inefficiencies costing over $1 million annually per warehouse. By leveraging operational data and developing custom AI and optimization models, Inveno aims to empower warehouse managers with precise, efficient, and scalable planning solutions. The founding team of Inveno consists of three members: - A warehouse operations expert with 8 years of experience at prominent logistics startups in the US and India. - A CEO with a track record of building and exiting three companies, as well as leading teams at Alibaba Group. - A CTO experienced in scaling engineering and systems across various international ventures. In terms of progress, Inveno's V1 product is scheduled to go live with the first client within 2 months. The startup has already secured a paid contract with a global multi-brand conglomerate and has a promising pipeline including some of the largest retailers in the US. As a data scientist joining the team, you will play a crucial role in leading the development of the core optimization engine, building machine learning models to support the optimizer, shaping the LLM interaction layer, and establishing MLOps best practices. Key responsibilities include architecting and implementing the core optimization engine, creating and deploying supervised learning models, collaborating with engineering on workflow design, and setting up model versioning, deployment, monitoring, and experimentation pipelines. Qualifications & Skills Required: - Experience in designing and deploying constraint-based optimization models using tools like Google OR-Tools, Gurobi, CPLEX, or similar. - Proficiency in advanced Python skills and familiarity with the data science stack including NumPy, pandas, and scikit-learn. - Strong foundation in supervised machine learning, encompassing feature engineering, model selection, and validation techniques. - Demonstrated ability to translate complex operational problems into solvable mathematical or machine learning models. - Bachelor's or Master's degree in Computer Science, Operations Research, Statistics, or a related quantitative field. Joining Inveno as a Data Scientist presents a significant opportunity for career advancement by taking ownership of the development and deployment of a foundational model that drives innovation in a critical sector.,