Data Scientist

Requirements

• You enjoy learning and are open to new ways of doing things
• You are not afraid to be yourself, experiment, make mistakes and learn from them, ask questions, or voice your concerns
• When communicating you are self‑aware, insightful, and proactive
• You are a team member first and individual contributor second. You are aware that high‑performing teams are only as strong as their weakest link
• You believe in continuous improvement and request frequent feedback from others
• Experience self‑managing projects and deliverables
• Experience working on NLP, LLM, and causal imprints
• Hands on experience with search, recommendation engines, forecasting, causal imprints, etc
• Detailed knowledge of data structures and database operations
• Problem‑solving skills and the ability to work on complex issues requiring innovative solutions
• Effective communication and collaboration skills when partnering with stakeholders and team members to resolve ambiguity in data science projects
• 3+ years of hands‑on, professional experience in data science, machine learning, or a related field, with a proven track record of delivering impactful data science projects
• Strong SQL and Python skills

• As a Data Scientist, you will play a pivotal role in our Data Science and Machine Learning (DSML) team, contributing to technical delivery of strategic projects from inception to implementation
• You will apply your experience in data science, machine learning, and statistical analysis to solve complex challenges, enhance our product offerings, and deliver actionable insights that propel our business forward
• This role requires a blend of technical proficiency and collaboration to help DSML deliver impactful work
• Develop algorithms and models from the experimental and prototyping phases all the way through to their use in customer‑facing solutions
• Collaborate with data scientists and machine learning engineers to define technical product requirements
• Establish performance metrics, build test suites, and create visualizations that effectively track model behavior
• Communicate complex data‑driven insights and recommendations to technical and non‑technical stakeholders