Data Science Manager - (Ref: 197922)

Forsyth Barnes; Arkansas; Hybrid; USD 216,000 - 264,000; Full time

Job summary

Forsyth Barnes is partnering with a large US retailer to hire a Data Science Manager in Arkansas. The role leads a data science team, shaping analytics that drive commercial performance across multi-channel environments.

You will guide technical direction, manage stakeholders, and ensure models deliver tangible business value while maintaining responsible data practices and scalable solutions.

Qualifications

• Recent experience leading data science teams in a complex commercial setting.
• Proven ability to translate business questions into analytical solutions.
• Strong track record of delivering predictive models and analytics products.

Responsibilities

• Set direction for a portfolio of data science initiatives tied to commercial performance and customer outcomes.
• Coach and develop data scientists with clear objectives and feedback.
• Translate business questions into structured analytical approaches and measurable success criteria.
• Oversee design, validation, deployment and improvement of predictive models and analytics solutions.
• Partner with product, technology, merchandising, operations, finance and senior stakeholders to prioritise opportunities and remove barriers.
• Establish practices for experimentation, monitoring, documentation, reproducibility, and responsible data use.
• Present findings clearly to enable timely executive decisions.
• Identify opportunities to scale solutions across stores, channels, and markets.

Skills

Data Science

Team leadership

Stakeholder management

Statistical modeling

Python

SQL

Cloud platforms

Tools

AWS

Azure

GCP

ML frameworks

Job description

Job Title: Data Science, Manager (Ref: 197922)

Location: Arkansas, Hybrid

Type: Permanent

Salary: $240,000 + Benefits

Overview – Data Science Manager

Forsyth Barnes are partnering with a large US retailer that is looking to hire a Data Science Manager to join its growing Data & Analytics organization. The Data Science Manager will lead the development and application of data science capabilities against high-value business priorities across a large, multi-channel retail environment. This role combines people leadership, technical direction, stakeholder engagement, and delivery ownership, ensuring that models and analytical products address clearly defined customer, commercial, and operational needs.

Success will involve establishing strong problem-framing practices, improving the reliability and usefulness of data science outputs, and helping business leaders act confidently on evidence.

Key Responsibilities – Data Science Manager

• Set the direction for a portfolio of data science initiatives linked to commercial performance, customer outcomes, and operational effectiveness.
• Lead, coach, and develop data scientists through clear objectives, regular feedback, and high standards for analytical quality.
• Translate ambiguous business questions into structured analytical approaches, modelling strategies, and measurable success criteria.
• Oversee the design, validation, deployment, and ongoing improvement of predictive models and advanced analytical solutions.
• Partner with product, technology, merchandising, operations, finance, and senior business stakeholders to prioritise opportunities and remove delivery barriers.
• Establish effective practices for experimentation, model monitoring, documentation, reproducibility, and responsible data use.
• Present complex findings in a clear, commercially relevant manner that supports timely executive and operational decisions.
• Identify opportunities to scale successful data science solutions across stores, digital channels, markets, and customer touchpoints.

Key Requirements – Data Science Manager

• Must have recent experience working for a retail, consumer of manufacturing organizations
• Substantial experience delivering data science, machine learning, or advanced analytics in a complex commercial or technology environment.
• Experience leading and building teams, preference covering both onshore and offshore
• Demonstrated success managing, mentoring, or technically leading data science professionals and multidisciplinary delivery teams.
• Strong practical knowledge of statistical modelling, predictive analytics, experimentation, and machine learning methodologies.
• Proficiency with relevant programming and analytical tools, such as Python, SQL, cloud platforms, and modern data science frameworks.
• Experience influencing senior stakeholders and explaining technical trade-offs, risks, and recommendations to non-specialist audiences.