Sr. Manager Data Sciences - Forecasting

• Implement best practices for MLOpsformodel deployment and monitoring

• Experiment with cutting edge technology such as generative AI, transformers, and other techniques to improve model metrics

• Translateforecasting outputsinto business-ready insightsfor decision-makers in R&D, finance, and commercial functions

• Optimize cost and ROI tradeoff to deliver high impact outputs (GPU/CPU utilization, memory allocation, tech overhead)

Must-Have Skills

• Proven experience delivering large-scale forecasting solutions that drive measurable business outcomes

• At least 3 years experience of managing AI/ML teams

• Expert in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

• Advanced proficiency in designing, evaluating, and applying a variety of supervised and unsupervised machine learning models to drive business value

• Experience with Generative AI models (e.g., GPT, DALLE, Stable Diffusion) and their applications across domains in forecasting

• Experience with Databricks platform for data analytics and MLOps

• Proficiency in state-of-the-art machine learning tools, such as deep learning frameworks, transformer models, NLP models, time series models and Bayesian models, with demonstrated and interpretable insight and impact

• Exceptional stakeholder management; can translate complex technical concepts into concise, outcome-oriented narratives

Nice-to-Have Skills:

• Experience in Biotechnology or pharma industry is a big plus

• Published thought-leadership or conference talks on enterprise GenAI adoption.

• Masters degree in computer science and/or data science

• Familiarity with Agile methodologies and Scaled Agile Framework (SAFe) for project delivery.

Education and Professional Certifications

• Masters degree or Bachelors degree in Computer Science, Business, Engineering, IT or related field
• 13+ Years of relevant work experience
• Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus

Soft Skills:

• Excellent analytical and troubleshooting skills

• Strong verbal and written communication skills

• Ability to work effectively with global, virtual teams

• High degree of initiative and self-motivation

• Ability to manage multiple priorities successfully

• Team-oriented, with a focus on achieving team goals

• Ability to learn quickly, be organized and detail oriented

• Strong presentation and public speaking skills.