Mercor

Mercor

Project Manager, Data Team

San Francisco

Sponsorship not specifiedDetected 10 days ago
Data EngineeringData ScienceProject ManagementStakeholder ManagementProcess ImprovementLeadershipCommunication

About the role

  • You'll be the connective tissue across data engineering, analytics, and cross-functional stakeholders, ensuring every project is delivered on time, within budget, and at the level of quality our clients and internal teams expect.
  • Take direct responsibility for the successful execution of projects, including meeting project goals, client/stakeholder service, quality of work, resource utilization, and profitability.
  • Serve as the primary coordination point across functional teams (Data Engineering, Analytics, Legal, Finance, etc.), aligning workstreams and driving decisions and accountability against timelines.

Responsibilities

  • Own end-to-end project management for data initiatives, including intake and scoping, requirements gathering, readiness reviews, cross-functional approvals, and launch/post-launch handoff.
  • Partner with team leads to vet, scope, and kick off assignments, and own all due dates and milestones.
  • Develop and maintain accurate project documentation, including timelines, budgets, and scoping documents.
  • Lead communications and change management across the project lifecycle, from kickoff briefings for stakeholders through end-user notifications ahead of launches, ensuring the right people have the right information at the right time.
  • Anticipate and manage the downstream implications of project decisions before they create risk
  • Build and continuously improve the infrastructure that makes data project delivery scalable: intake forms, templates, checklists, SOPs/playbooks, and retrospectives that feed into process improvement.
  • Manage relationships with key stakeholders to promote trust and future opportunities.

Requirements

  • 3-5+ years of project management experience or related experience.
  • Bachelor's degree or equivalent experience in a related field.

Nice to have

  • Proven track record managing large, cross-functional data or technical projects.
  • Experience managing a high volume of projects in parallel.
  • Experience with data, engineering, or analytics project types.
  • Free Equinox membership

Skills

  • Excellent leadership, communication, and stakeholder management skills.
  • Ability to work collaboratively across departments (engineering, data science, leadership, legal, finance).
  • Superb attention to detail, sound judgment, and strong listening skills.
  • Comfortable driving process improvement and proposing more efficient ways of working.
  • Passion for data-driven products and cross-functional collaboration.
  • Knowledge, Skills, & Abilities:

Compensation

  • Bi-annual performance bonus structure

Benefits

  • Bi-annual performance bonus structure
  • Generous equity grant vested over 4 years
  • Up to $15k Relocation bonus
  • $10K housing bonus (if you live within 0.5 miles of our office)
  • $1.5K monthly stipend for meals
  • $200 monthly laundry reimbursement
  • $200 monthly personal wellness reimbursement
  • Health, Dental, Vision insurance
  • Lead, motivate, and build a strong team environment for project contributors, inspiring a shared vision, enabling others to act, and taking ownership of team outcomes.

Company info

  • by sharing knowledge, experience, and context that can't be captured in code alone.
  • Today, more than 30,000 experts in our network collectively earn over $3 million a day.
  • Mercor is creating a new category of work where expertise powers AI advancement.
  • Achieving this requires an ambitious, fast-paced and deeply committed team.
  • You'll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.
  • Mercor is a profitable Series C company valued at $10 billion.
  • We work in-person five days a week in our San Francisco, NYC, or London offices.

This listing is sourced directly from Mercor's careers page and normalized into a canonical job model.