Principal Data Scientist

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AbbVie Kft.
Munkavégzés helye

Országos lefedettség

Munkaidő, foglalkoztatás jellege
- Alkalmazotti jogviszony
- Általános munkarend
Elvárások
- Angol középfok
- 5-10 év tapasztalat
- Főiskola

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Responsibilities

Lead a portfolio of advanced analytics capabilities across customer understanding, engagement planning, decision support, and measurement
Translate product requirements and business goals into scalable technical solutions, including model design, feature engineering, validation, and deployment
Lead the design and development of predictive and inferential models that generate actionable insights on customer behavior, engagement opportunities, and drivers of business performance using complex, multi-source data
Design analytics approaches that evaluate cross-channel engagement patterns, interaction effects, and temporal dynamics to inform coordinated customer strategies
Own measurement methodologies to measure effectiveness, incrementality, and business impact using experimental and observational methods
Partner with BTS, Digital Lab, engineering, and platform teams to build scalable, production-ready analytics and AI/ML solutions
Establish best practices in model development, including code quality, documentation, reproducibility, peer review, version control, and methodological rigor
Synthesize complex technical findings into clear, actionable insights and recommendations for non-technical stakeholders
Partner with engineering and platform teams to productionalize AI/ML solutions, including deployment, monitoring, and lifecycle management
Stay current with advances in applied machine learning, causal inference, and pharmaceutical analytics, proactively identifying and piloting emerging methods that could enhance the existing and new capabilities
Provide technical mentorship and hands-on guidance to junior and mid-level data scientists supporting the advanced analytics team
Lead technical workstreams with external analytics vendors and partners, including oversight of deliverable quality and methodology validation

Requirements

Bachelor’s degree in statistics, mathematics, computer science, engineering, or another quantitative discipline
Master’s or PhD in a quantitative field strongly preferred
8+ years of experience in data science, machine learning, or advanced analytics with delivery of production-quality models and solutions
5+ years of experience in pharmaceutical, biotech, healthcare, or life sciences commercial analytics highly preferred
4+ years of experience in omnichannel analytics including journey analysis, touchpoint measurement, engagement optimization, or next-best-action modeling
4+ years of experience measuring commercial effectiveness and business impact using methods such as promotional response analysis, closed-loop measurement, A/B testing, and quasi-experimental techniques
Strong proficiency in Python and/or R and strong SQL skills
Hands-on Python experience with pandas, NumPy, scikit-learn, and PySpark for data transformation, feature engineering, model development, and scalable workflows
Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow for sequential, temporal, or recommendation use cases
Experience working with product owners, business stakeholders, and cross-functional teams to translate requirements into technical solutions
Experience productionizing AI/ML solutions in cloud environments including deployment, monitoring, and lifecycle management

Nice-to-have

Experience with advanced ML and optimization methods including reinforcement learning, multi-armed bandits, transformers, and other deep learning approaches for sequential, recommendation, or next-best-action use cases
Familiarity with pharmaceutical data sources such as IQVIA, Symphony Health, APLD, or similar Rx, claims, and engagement datasets
Experience working in agile product development environments
Exposure to cloud ML platforms and MLOps tools such as Azure ML, Databricks, and MLflow
Experience presenting analytical methods and findings to senior or executive audiences
Exposure to modern AI engineering approaches including LLM-based workflows, orchestration frameworks, or agentic AI patterns
Experience integrating AI/ML solutions using APIs, pipelines, or orchestration tools

What we offer

Comprehensive package of benefits including paid time off (vacation, holidays, sick)
Medical, dental, and vision insurance
401(k) to eligible employees
Eligibility to participate in long-term incentive programs

Company info

AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio.