Senior Project Manager

Altimetrik Poland is a digital enablement company. We deliver bite-size outcomes to enterprises and start-ups from all industries in an agile way to help them scale and accelerate their businesses. We are unique in Poland's IT market. Our differentiators are an innovation-first approach, a strong focus on core development, and an ability to attack the challenging and complex problems of the biggest companies in the world.

We are looking for a highly experienced Project Manager with 15+ years of expertise in delivering complex Data & AI initiatives within the Life Sciences and Healthcare sector. The ideal candidate brings a rare combination of strong project governance, deep life science domain knowledge, and hands-on familiarity with data engineering, machine learning, and AI platforms. You will lead end-to-end delivery of data transformation and AI adoption programs for pharmaceutical, biotech, CRO, and health-tech organizations — on time, within scope, and with measurable business impact.

Project Planning & Governance

Lead end-to-end project management of Data & AI programs — from initiation and discovery through delivery, hypercare, and transition to BAU.

Define project scope, objectives, milestones, and success criteria in collaboration with business sponsors, data engineering, and AI teams.

Develop comprehensive project plans, resource plans, RACI matrices, risk registers, and communication plans for multi-stream data initiatives.

Establish and enforce project governance frameworks: steering committee cadence, RAID logs, change control processes, and escalation protocols.

Manage project budgets from $500K to $10M+; track actuals vs. forecasts and deliver cost-efficiency initiatives.

Drive delivery using hybrid methodologies — Agile (Scrum/Kanban) for data development sprints and Waterfall for regulatory and validation workstreams.

Data & AI Program Delivery

Oversee delivery of data platform modernization programs: data lake/lakehouse migrations, cloud data warehouse implementations (Databricks, Snowflake, AWS, Azure), and data pipeline development.

Manage AI/ML project lifecycles — from use case identification, data readiness assessment, model development, and validation through production deployment and monitoring.

Coordinate delivery of Generative AI and LLM-based solutions for life science applications: regulatory document automation, clinical trial analytics, pharmacovigilance signal detection, and drug discovery support.

Govern data migration programs including legacy system decommissioning, data cleansing, ETL pipeline build, and data reconciliation.

Ensure traceability and auditability of all data and AI deliverables in line with GxP, 21 CFR Part 11, and CSV/CSA requirements.

Stakeholder Management & Communication

Serve as the primary point of contact for C-suite sponsors, VP-level business owners, and external vendors across all project workstreams.

Facilitate executive steering committee meetings, project working groups, and cross-functional workshops with pharma, biotech, and CRO stakeholders.

Translate complex technical data and AI concepts into clear business language for non-technical senior leaders and regulatory audiences.

Manage relationships with third-party technology vendors, system integrators, and cloud providers (AWS, Azure, GCP, Databricks, Snowflake).

Prepare and present project status reports, executive dashboards, and milestone updates to internal and client leadership.

Risk, Quality & Change Management

Proactively identify, assess, and mitigate project risks specific to data quality, AI model performance, regulatory compliance, and system integration.

Lead change management activities to drive adoption of new data platforms and AI tools across clinical, regulatory, and commercial teams.

Manage scope creep, competing priorities, and resource constraints across concurrent data and AI workstreams.

Conduct post-project retrospectives, lessons learned sessions, and contribute to PMO best practices and delivery playbooks.

Ensure all project deliverables meet quality standards through structured review, UAT coordination, and sign-off processes.

Lead cross-functional delivery teams of 10–50+ members: data engineers, ML engineers, data scientists, business analysts, QA leads, and domain SMEs.

Manage third-party vendor contracts, SLAs, and performance — including offshore/nearshore delivery teams.

Coach and mentor junior project managers and business analysts; contribute to PMO capability development.

Foster a collaborative, high-performance delivery culture aligned with agile and continuous improvement principles.

Project Management Expertise

15+ years of project management experience, with 5+ years leading Data & AI programs in Life Sciences or Healthcare.

Proven track record delivering large-scale data platform, analytics, ML, and AI projects ($1M–$5M+ budgets, 12–36 month durations).

Expert proficiency in Agile (Scrum, SAFe, Kanban) and Waterfall/hybrid methodologies; experienced in mixed-methodology program delivery.

Strong command of project management tools: JIRA, Confluence, MS Project, Smartsheet, Azure DevOps, or equivalent.

Experienced with PMO governance: portfolio reporting, resource management, dependency tracking, and benefits realization.

Life Sciences Domain Knowledge

15+ years of experience in pharma, biotech, CRO, medtech, or health IT — with deep understanding of drug development lifecycle.

Hands‑on experience managing GxP‑regulated projects: CSV/CSA, IQ/OQ/PQ validation, audit trail requirements, and 21 CFR Part 11 compliance.

Familiarity with life science platforms: Veeva Vault, Medidata Rave, Oracle Clinical, SAS, and laboratory information management systems (LIMS).

Data & AI Literacy

Strong working knowledge of modern data architectures: data lakehouse, cloud data warehouse, ETL/ELT pipelines, and data mesh.

Familiarity with key platforms: Databricks, Snowflake, AWS (S3, Glue, Redshift, SageMaker), Azure (Synapse, ADF, Azure ML), or GCP.

Understanding of ML/AI lifecycle: data preparation, model development, validation, deployment, monitoring, and MLOps.

Awareness of Generative AI, LLMs, and RAG pipelines — able to facilitate technical discussions and scope AI initiatives with engineering teams.

Leadership & Communication

Exceptional stakeholder management skills — credible and confident with C-suite executives, regulatory bodies, and technical delivery teams.

Strong written and verbal communication; ability to produce executive presentations, status reports, and regulatory documentation.

Demonstrated experience leading globally distributed, cross-functional teams across time zones and cultures.

Skilled negotiator and conflict resolver — able to align competing priorities across business, IT, and compliance functions.

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