Data Scientist

Location: Atlanta, Hybrid, 3 days per week in office

Salary: $140,000 to $150,000 base + Bonus

We are supporting a leading consumer goods technology organisation that is looking to hire a Data Scientist to help modernise existing production ML and analytics applications.

This is a data science first role, suited to someone with strong fundamentals who enjoys working with real business problems, imperfect data and production models. The successful candidate will help improve existing models, build new solutions and work closely with data science, engineering, product and business teams to drive adoption and measurable value.

This is not a narrow task based role. The team is looking for someone who can understand the problem, explore the data, build practical models and think through how those models create value in a live business environment.

• Assess and improve existing data science models across recommendation and product availability use cases
• Carry out exploratory data analysis to understand business problems, data quality and model opportunities
• Build, test and improve ML models using Python, SQL and modern data science techniques
• Develop strong feature engineering approaches using imperfect and complex business data
• Work with data engineering and platform teams to understand how data is structured, consumed and prepared for ML models
• Support the full model lifecycle from problem discovery and development through to production, adoption and improvement
• Monitor model performance, identify areas for improvement and help increase accuracy, reliability and business trust
• Partner with business stakeholders to understand priorities, adoption challenges and value measurement
• Work as part of a small product style team, taking ownership rather than waiting for narrow tasks

• 4 plus years’ experience in data science, applied ML or production analytics
• Strong Python, SQL, modelling, EDA and feature engineering skills
• Experience working with production models or full model lifecycle exposure
• Ability to work with imperfect data and solve practical business problems
• Strong understanding of core ML concepts, model types and algorithm selection
• Azure, Databricks or similar cloud platform experience beneficial
• CPG, retail, supply chain, customer analytics or churn modelling experience beneficial
• Strong communicator with an ownership mindset, not a narrow task taker