Data Scientist

Required Skills & Experience • 5–7 years of experience as a Data Scientist, Machine Learning Engineer, or similar role. • Strong foundation in classical machine learning, statistical modeling, and regression methods. • Educational background in Statistics, Mathematics, Computer Science, Engineering, or a related quantitative field. • Hands‑on experience with at least one of the following: PyTorch TensorFlow PySpark • Snowflake preferred, databricks is okay as well • Experience with GenAI concepts, tools, or applied use cases. • Strong experience preparing, wrangling, and transforming structured datasets. • Ability to work independently with minimal direction while managing multiple analytical workstreams. • Excellent communication, data storytelling, and stakeholder‑management skills. Job Description We are seeking a highly skilled Senior Data Scientist with strong expertise in classical machine learning, regression modeling, and statistical predictive analytics. This role is ideal for someone with a statistics-focused educational background (or similar quantitative discipline) who can independently drive model development, translate business needs into analytical solutions, and deliver impactful insights to stakeholders. You will work extensively with structured hospitality data to build features, develop predictive models, and support sales and service–focused use cases. This is a highly independent, creative role requiring strong communication, storytelling, and stakeholder partnership skills. Responsibilities include: • Develop, test, and deploy classical machine learning models, with a core focus on regression-based predictive modeling. • Prepare, clean, and transform structured data to build high‑quality features for modeling. • Collaborate regularly with cross‑functional stakeholders to understand business goals, clarify requirements, and align analytical work with strategic needs. • Own end‑to‑end development of sales and service–specific use cases, from discovery to deployment. • Communicate complex analytical findings in a compelling, accessible way to both technical and non‑technical audiences. • Explore and apply GenAI techniques as they enhance modeling, efficiency, and analysis workflows. • Work independently to structure analytical approaches, evaluate methods, and recommend model‑driven solutions.