Data Scientist

Company Description

Inhabitr brings together advanced technology, operational excellence, and sustainable, elegant design to create spaces tailored to each client’s vision. The company specializes in streamlined FF&E procurement, ensuring projects are delivered on schedule, aligned with brand standards, and within budget. Inhabitr partners with clients across sectors to maximize the functional and aesthetic potential of every environment. The team is headquartered in San Francisco and Mumbai, with a focus on innovation, design quality, and reliability for its project portfolio.

Role Description

The Data Scientist role at Inhabitr is a full-time, on-site position based in San Jose, CA. The individual in this role will collect, clean, and analyze structured and unstructured data from various business systems to support decision-making across operations, design, and procurement. Day-to-day responsibilities include building and validating statistical and machine learning models, performing exploratory data analysis, and developing dashboards and visualizations to communicate insights to stakeholders. The Data Scientist will collaborate with cross-functional teams to identify data-driven opportunities to improve forecasting, pricing, inventory management, and project delivery. This role also involves documenting methodologies, presenting findings, and continuously refining models and analytics processes as new data becomes available.

Qualifications

• Strong foundation in Data Science and Statistics, including model development, hypothesis testing, and experimental design.
• Proficiency in Data Analytics and Data Analysis for transforming raw data into actionable insights and recommendations.
• Experience with Data Visualization tools and techniques to create clear, compelling dashboards and reports.
• Hands‑on experience with programming languages such as Python or R, and familiarity with SQL for querying and managing data.
• Knowledge of machine learning libraries and frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and practical experience applying them to business problems.
• Ability to work with large datasets, including data cleaning, feature engineering, and performance optimization.
• Strong communication skills to explain complex analytical findings to non-technical stakeholders and support data-informed decisions.
• Bachelor’s or Master’s degree in a quantitative field such as Data Science, Statistics, Computer Science, Mathematics, or a related discipline.
• Experience in domains such as operations, supply chain, or design-focused businesses is beneficial but not required.