Associate Director - AI Machine Learning Engineer

Digital Core is actively looking for an AI Machine Learning Engineer to spearhead our efforts in the development and deployment of machine learning models that enhance predictive analytics and decision-making across multiple processes and systems in pharma. Are you passionate about artificial intelligence and the impact it can have across an entire industry? Are you a change agent who can influence organizations?

If so, bring YOUR skills and talents to Lilly where you’ll have the chance to create an impact on the lives of patients!

• Machine Learning Model Development:
  Design, build, and implement state-of-the-art machine learning models to improve product offerings and operational efficiency. Utilize a variety of data sources and machine learning algorithms to create scalable solutions for complex problems.
• Data Strategy and Analytics:
  Lead the creation of sophisticated analytics frameworks to mine data sets, identify trends, and provide actionable insights. Collaborate with data engineers and scientists to refine data collection and preprocessing techniques.
• Model Optimization and Evaluation:
  Continuously test, refine, and enhance the accuracy of machine learning models using robust methodologies. Implement A/B testing frameworks to compare model performances and optimize based on specific KPIs.
• Cross-Functional Collaboration:
  
  Work closely with product managers, software engineers, and business analysts to integrate machine learning models into broader tech and business strategies, ensuring alignment with company objectives and market needs.
• Ethics and Compliance in AI Development:
  Uphold high standards of integrity and compliance in the development and deployment of machine learning models, adhering to ethical AI practices and regulatory requirements.

• Problem Solving with Advanced Analytics:
  Use your analytical skills to unravel complex challenges, applying machine learning techniques to develop innovative, data-driven solutions.
• Technical Proficiency:
  Combine your deep understanding of machine learning, statistics, and data science with practical experience in programming languages such as Python or R.
• Effective Communication:
  Clearly communicate complex machine learning concepts and the results of analyses to stakeholders, enhancing strategic decision‑making across the company.
• Adaptive Learning:
  Stay abreast of the latest advancements in machine learning, data science, and related technologies, continuously adapting to new tools and methodologies to maintain competitive and technological edge.
• Leadership in Project Execution:
  Drive projects from conception to completion, providing technical leadership and collaborative project management to ensure timely delivery of machine learning solutions.

• Proven Experience in Machine Learning:
  Extensive experience developing, deploying, and maintaining machine learning models in a professional setting. Familiarity with neural networks, regression models, clustering, and decision tree algorithms.
• Strong Statistical Background: A deep understanding of statistical analysis, probability theory, and data modeling techniques.
• Proficient Coding
  
  Skills:
  
  Expertise in Python, R, or similar programming languages, and familiarity with machine learning libraries such as scikit‑learn, Tensor Flow, or PyTorch.
• Data Manipulation Expertise:
  Ability to work with large data sets and proficient use of SQL and data manipulation tools.
• Collaborative and Ethical Mindset: A strong team player with a proven track record of ethical decision‑making and compliance in AI development.

• Master’s degree in computer science, engineering, mathematics, or a related field.
• 2+ years of experience in machine learning or data science roles.
• Experience with AI and machine learning technologies including supervised and unsupervised learning, deep learning, and neural networks.

• Experience in working with AI technologies and tools, such as natural language processing (NLP), AI generation, machine learning algorithms, deep learning, etc. and delivering end-to-end solutions to business stakeholders…