Manager, Data & AIVerified as a real position

Who we’re looking for

• 5+ years of professional experience in data science, data engineering, or analytics engineering, with at least 2 years leading a team of data scientists or data engineers.
• Demonstrable hiring track record. You have personally hired multiple senior data scientists or engineers who turned out to be strong performers.

What you’ll do

• Shape the Team and Make It Real
• The roles are defined and hiring is moving. Your job is to make sure the right people land in the right seats, onboard well, and become a team rather than five individual hires.
• Step into the live hiring loop fast. Calibrate the bar, run final-round interviews personally, and own the close on every offer from your first week.
• Decide which open seat each strong candidate fits into. The roles are roughly scoped, not rigid — part of your job is matching the actual people you hire to where they will do the best work.
• Onboard deliberately. Each new hire should know inside the first two weeks what they own, what success looks like in 90 days, and who their key partners are in Product, Operations, and CX.
• Hire the AI Consultant with extra care. This is not a junior role and not a generic ML engineer. You are looking for someone who can walk into a CX or Ops meeting, find a real problem, and ship something useful within weeks.
• Every new req, and every existing req in flight, carries a documented ROI justification tied to a specific project. You take ownership of this from day one: validate what is already in the pipeline, kill what does not hold up, and orchestrate new reqs cleanly with the PM, Finance, and Recruiting.
• Sell ShipMonk and the team externally. Show up in the Prague data community, write, speak, and be visible. You are a hiring magnet, not just a hiring manager.
• Find the Team's Place in the Org
• A new team inside an existing engineering org does not have its place by default. You have to define it.
• Establish how the team works with Platform on shared infrastructure, with Product on roadmap intake, with Operations and CX on use-case discovery, and with Finance on capitalization and ROI reporting.
• Define what the team owns, what it consults on, and what it explicitly does not do. Write it down.
• Build the relationships that make the above work. The first six months of stakeholder trust are disproportionately important.
• Set Direction and Translate Strategy into Delivery
• Take the company strategy and the SVP of Engineering's priorities and turn them into a concrete v1 roadmap and OKRs. Predictive routing and VCN optimization, IMS data products, and the AI Consultant's use cases all compete for the same team capacity from day one. Make the trade-offs explicit and defensible.
• Run a transparent quarterly OKR cycle: set, communicate, review, course-correct. Surface what you killed, not just what you shipped.
• Own the cross-team contract with Product, Operations, CX, and Finance. When dependencies slip, escalate early, in writing, with options.
• Set the AI Agenda
• You own the AI agenda for the data function. The AI Consultant works for you, but the strategy comes from you.
• Decide where AI changes the economics of how ShipMonk runs and where it doesn't. Cut through hype.
• Define the intake process: how teams across CX, Operations, and Product request help, how you triage, how you decide what's worth doing.
• Co-own the AI roadmap with Product and Operations. Push back when a request is a feature in disguise or a science project with no business case.
• Make the wins visible, measurable, and reusable. One-off automations are fine; repeatable patterns are better.
• Drive AI-assisted development across the team. Claude Code, Cursor, Copilot, and our internal Claude skills are real productivity levers, not slogans. Set expectations, share what works, remove friction. You lead by using these tools yourself, daily.
• Own Delivery, Quality, and Production
• Be accountable for what your team ships, when it ships, and how it behaves in production. Models that drift, pipelines that fail silently, and dashboards no one trusts are all your problem.
• Define and track the metrics that matter from the start: model performance in production, pipeline reliability, time from idea to deployed model, business impact per project.
• Set engineering standards (code review, testing, observability, documentation) early. Standards are easier to set on day one than to retrofit on day 300.
• When there is a major incident in your area, you own the response, the postmortem, and the systemic preventive action. Change the system, never blame the person.
• Run a Business-Oriented Data Team
• Know your domain's economics. Be able to state, in plain language, how transportation data products affect routing margin and how IMS data products affect placement cost and stockouts.
• Frame technical investment in business terms: margin gained, cost avoided, support tickets reduced, revenue protected. "Better model accuracy" alone is not a justification at this level.
• Own quarterly ROI reporting to leadership against each project's business case. Move the team from "insights on a slide" to "logic in the code, dollars on the page."
• Partner with Finance on build-vs-consult tracking so internal software work stays capitalizable.
• Develop the People You Hire
• Run an honest performance cycle from the first review. Give candid feedback often, write reviews that someone could actually use to grow, and act decisively when someone is not performing.
• Grow your senior ICs into tech leads and your AI Consultant into someone with cross-company influence. Internal promotions inside year two should be believable to people outside the team.
• Be approachable and consistent. Direct reports, peers, and stakeholders should all find you the same person on a good day and a bad day.
• Live the ShipMonk Values
• Own It: if something is broken in your area, a model, a pipeline, a stakeholder relationship, a handoff, it is yours to fix, even if you did not cause it.
• Merchant First: when there is a trade-off between technical elegance and merchant impact, lean merchant-first and document why.
• People Make ShipMonk: invest in the people you hire. Give and receive feedback with candor and respect. Challenge ideas, not people.
• Change the Score: treat every incident, missed deadline, or attrition event as a systemic signal, not individual blame.
• Get Shit Done: debate, commit, move on. Once a decision is made, execute.

About the position

ShipMonk isn't just a 3PL; we're a growth partner for merchants . We provide cutting- edge technology and a network of owned and operated fulfillment centers that empower high-growth ecommerce and DTC brands to stress less and grow more. With over 2,500 employees across five countries, we're on a mission to revolutionize fulfillment by providing everything from the fastest click-to-delivery and real-time inventory to custom solutions—all with a merchant - first mindset.

Benefits

• Global Fulfillment Network: Our 12+ owned and operated fulfillment centers span the US, Canada, Mexico, the U.K., and Mainland Europe. We never outsource, ensuring quality and consistency.
• Proprietary Technology: We've eliminated the need for tribal knowledge with our AI-powered platform. It provides a real-time, unified view of inventory and orders, giving our merchants the control and visibility they need to succeed.
• Unrivaled Support: We provide hands-on, "mom and pop" support with a global reach. Our dedicated teams are on-site at every fulfillment center, ready to jump into action.
• Transparent Pricing : We believe in honest, long-term partnerships. Our all- inclusive pricing means predictable costs, with no hidden fees or surprises.
• Committed to the Future: We invest over $10 million annually in research and development to ensure our technology and services continually evolve, helping merchants plant roots with a partner who is here to stay.