Data Scientist (Ref: 196736)
- eTail
- Hybrid, Atlanta, United States
- permanent
- $ 150000.00 per annum
-
about the roleJob Description
Title: Data Scientist
Location: Atlanta, Hybrid, 3 days per week in office
Industry: Consumer
Salary: $140,000 to $150,000 base + Bonus
Overview
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.
Key ResponsibilitiesResponsibilities
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
RequirementsRequirements
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
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