Product Manager, AI & Planning Science

Description

The role owns the roadmap and delivery for the company's data science and machine learning products. The work covers two linked areas: planning science, including forecasting, inventory optimization, demand sensing, and the models that guide merchandising and supply chain choices; and customer and consumer analytics, including lifetime value, segmentation, and personalization models and data products. Agentic AI and generative AI projects may be added as the portfolio changes.

The job suits a product manager who can work closely with data scientists and ML engineers and turn detailed modeling work into tools that business teams use and trust. You keep delivery on track, make sure requirements reflect real business needs, and track results so the team knows whether the work is succeeding.

The company is an athletic apparel brand that designs clothing for training and for everyday wear, with a casual look inspired by an active coastal California lifestyle.

Responsibilities

• Keep the planning science and consumer AI roadmap current, ordered, and visible, balancing near-term delivery with longer-term model and platform work across both areas.
• Work with merchandising, supply chain, finance, marketing, e-commerce, and technology partners to find high-value data science and ML opportunities and add them to the roadmap through a clear prioritization process.
• Lead trade-off discussions between business stakeholders and data science teams so decisions rest on data and reflect what models can realistically deliver.
• Share roadmap status, sequencing changes, and delivery progress on a regular schedule so stakeholders are not caught off guard.
• Raise dependencies, data readiness gaps, and model risks early so teams can fix them before they block progress.
• Turn planning, operational, and customer needs into detailed product requirements, model evaluation criteria, and acceptance standards that data science and engineering teams can build against.
• Work with data scientists and ML engineers throughout development: clarify scope, review model outputs, agree on evaluation methods, and make quick decisions when requirements change.
• Make sure model outputs fit into business workflows and decision tools, so planners, marketers, merchants, and operators can actually use them.
• Run agile ceremonies that keep data science, engineering, analytics, and business teams aligned.
• Own launches from start to finish: rollout plans, user training, stakeholder communication, and post-launch monitoring to confirm performance.
• Apply the same delivery discipline to any agentic AI or generative AI projects.
• Build working relationships with merchandising, planning, supply chain, finance, marketing, and CRM teams to learn their workflows, data, and the decisions where better models would help most.
• Support customer analytics work such as lifetime value modeling, segmentation, churn prediction, propensity scoring, and personalization, making sure outputs are useful to marketing and e-commerce teams.
• Work with data scientists and analytics teams to track production model performance, including accuracy, drift, coverage, and business impact, across planning and consumer products.
• Gather stakeholder feedback, model performance data, and user behavior to keep a continuous improvement backlog.
• Represent end users of planning and consumer analytics products, pushing for outputs that are interpretable, trustworthy, and suited to the decisions they support.
• Give senior leadership regular updates and outcome summaries based on model performance and business results.

Requirements

• Bachelor's degree in business, computer science, statistics, engineering, or a related field, or equivalent experience (preferred).
• 8+ years of product management experience, including 3+ years working directly with data science or ML teams on products used by real customers in production.
• A proven record of running a roadmap and delivering data science or ML features end to end, with measurable results in planning, operations, or customer-facing areas.
• Ability to work with data scientists and ML engineers on modeling approaches, metric evaluation, and data needs at a meaningful level of detail.
• Experience turning business planning, forecasting, customer analytics, or operational needs into clear model requirements and product specs.
• Understanding of the full ML lifecycle (data preparation, model development, evaluation, deployment, and monitoring) and the product questions at each stage.
• Strong written and spoken communication, able to explain modeling work clearly to business, executive, and technical audiences.
• Strong organization and a consistent drive to act, while working comfortably with the uncertainty of data science delivery.
• Preferred: experience in retail, e-commerce, direct-to-consumer, or consumer goods, especially in planning and customer analytics.
• Preferred: familiarity with planning science topics such as demand sensing, replenishment optimization, size curve modeling, or markdown optimization.
• Preferred: familiarity with customer science topics such as lifetime value, segmentation, churn modeling, propensity scoring, or AI-driven personalization.
• Preferred: exposure to agentic AI, LLM-powered workflows, or generative AI in a business setting, through direct delivery or adjacent product work.
• Preferred: comfort using SQL, BI tools, or experimentation frameworks to assess model performance and product results on your own.
• Preferred: experience with ML platforms such as Azure ML, Databricks, SageMaker, or similar.
• Preferred: understanding of responsible AI for predictive models, including bias, fairness, explainability, and model governance.
• Preferred: a track record of staying current on new data science and AI techniques and bringing them into production with technical teams.

Conditions

The salary range is $137,300 to $176,610 per year.

This role is eligible for a bonus.

Applicants are considered under equal employment opportunity guidelines, and their information is kept confidential.

Benefits

• Health insurance.
• Savings and retirement plan.
• Employee assistance program.
• The company discount and industry perks.
• Paid time off.
• Wellness and fitness benefits.