- Company Name
- Lundbeck
- Job Title
- Data Scientist AI Analytics, Strategy, and Activation
- Job Description
-
**Job Title:** Data Scientist, AI Analytics, Strategy & Activation
**Role Summary:**
Design, develop, and deploy AI/ML models to support Lundbeck US’s AI strategy, drive commercial growth, and optimize business processes. Serve as a technical liaison between business stakeholders and AI teams, ensuring models deliver measurable value and align with strategic priorities.
**Expectations:**
- Deliver high‑quality AI solutions that meet defined business objectives.
- Maintain model performance post‑deployment and iterate based on evolving needs.
- Communicate technical concepts clearly to non‑technical audiences.
- Manage multiple projects, vendor resources, and cross‑functional collaborations.
- Stay current with AI research and apply emerging techniques where beneficial.
**Key Responsibilities:**
- Design, train, test, and implement AI/ML algorithms (including neural networks, reinforcement learning, unsupervised learning).
- Perform data exploration, preprocessing, feature engineering, and model fine‑tuning for production.
- Deploy models using cloud platforms and MLOps pipelines; monitor and improve performance.
- Document models, methodologies, and best practices; share knowledge across the organization.
- Translate business requirements into technical specifications; guide vendor or technical staff on issue resolution.
- Contribute to the overall AI strategy and identify new AI use cases across functions.
- Partner with Advanced Analytics and Omnichannel Customer Engagement teams to enhance operational efficiency.
- Support business requirement gathering, solution development, and implementation with cross‑functional teams.
**Required Skills:**
- Predictive modeling & machine‑learning techniques: clustering, multivariate regression/tree‑based analysis, neural networks, reinforcement learning, Bayesian/Monte Carlo/bootstrapping.
- Programming: Python, R, or Java.
- Experience with NLP, deep learning, and large language models (LLMs).
- Cloud platforms (AWS, Azure, GCP) and MLOps tools for model deployment.
- Version control (Git).
- Strong analytical, problem‑solving, and independent work capabilities.
- Excellent oral and written communication; ability to convey technical concepts to non‑technical stakeholders.
**Required Education & Certifications:**
- Bachelor’s degree in a quantitative discipline (e.g., Computer Science, Data Science, Statistics, Engineering, Mathematics, Economics) from an accredited institution.
- Minimum 4 years of experience in AI/ML model development, deployment, and optimization for marketing, sales, or commercial initiatives.
*Preferred (not required):* project leadership experience, pharmaceutical/biotech industry background, familiarity with pharmaceutical datasets (patient, claims, EHR, demand), knowledge of GxP/ALCOA+ regulatory standards.