Intelletec is partnered with a Fortune 8 company and is one of the largest providers of healthcare solutions, retail pharmacy, medical & pharmaceutical supplies, and specialty care in the United States.
They are seeking a Director of Machine Learning Engineer to provide the roadmap for MLOps CI/CD/CT strategy. They are looking for a candidate that is passionate about building machine learning applications that ensure patients receive the medications they need when they need them and provide value for our customers and the Data Science team.
- Own our MLOps CI/CD/CT strategy to standardize batch and streaming training and serving of ML Web apps and APIs.
- Create the roadmap for our next generation their data science tech stack.
- Recruit top talent machine learning engineers to join your team. Drive adoption of best-in-class capabilities, including Deep Learning, Natural Language Processing, and Next Best Action Recommenders.
- Build, scale, deploy, and manage data science solutions in a multi-cloud environment to provide predictive insights.
- Communicate strategy and results to technical and non-technical audiences; Develop and maintain strong relationships with key stakeholders, partners, and internal clients.
- Provide analytics leadership, conduct weekly methodology/code reviews, and Utilize industry and academic resources to continuously learn, innovate, and contribute to a growing knowledge base of data science best practices.
- Collaborate with multi-disciplinary team members (data scientists, data engineers and business analysts); Manage business stakeholder relationships to drive action and value from data science insights
- Partner with digital accelerators, universities, and consultants to accelerate innovation; Opportunities to co-author peer-reviewed publications and patent your AI/ML innovations
- Understand their complex and diverse data environment to design data strategy for use in machine learning models; Analyze complex health, business transaction, and supply chain datasets
- Solve problems from the business point of view, build and execute solid analytics work plans, gather and organize large and complex data assets, perform relevant analyses (data exploration and statistical modeling), automate work streams, foster teamwork in interactions, develop client relationships with business stakeholders, and communicate hypotheses and findings in a structured way.
- 9 years of relevant experience in machine learning; and software engineering, architecture and design is required.
- +3yrs management and mentorship experience with machine learning engineers/data scientists in business or scientific research settings.
- Expert experience in one or more programming languages, Python plus Java, C/C++, ...
- Expert experience with MLOps, CI/CD/CT, and scalable ML deployment (e.g. MLFlow, Kubeflow, Docker, Kubernetes)
- Expert experience with cloud computing in Azure or GCP
- Experience with distributed computing: (e.g. Databricks, Apache Spark, Hadoop...)
- Experience with data pipelines, streaming architecture (Kafka), data engineering, creating feature stores, and processing unstructured and structured data at scale.
- Industry experience using TensorFlow and Pytorch to develop Representation Machine Learning Systems; e.g. Next-Best-Action, Recommendation systems; Deep Learning Neural Networks; Image understanding; Document classification and keyword extraction
Additional Knowledge & Skills:
- Industry experience in Healthcare or Supply Chain, including project and budget management
- Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g. regression, classification, Time Series analysis: e.g. ARIMA, Traditional machine learning methods: e.g. Random Forest, ensemble model techniques, Optimization: e.g. linear programming
- Experience with Linux, shell scripting
- Experience with Snowflake Data Cloud
- Familiarity with a data visualization tool: e.g. Tableau, Power BI
- Experience with Reinforcement Learning for inventory optimization and marketing
Please reach out to email@example.com for more info!