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Data Science Team Leader

Position Summary:  

Direct Supply is building the future of healthcare technology with industry-leading products, solutions and platforms to help improve the lives of millions of seniors and those who care for them. 


In the  Data Science Team Leader  position, you’ll apply your expertise in Generative AI and Machine Learning Operations (MLOps) to develop and deploy advanced generative AI models. Your focus will be on creating impactful data and content solutions to address key business challenges while strategically implementing these technologies. Your responsibilities will include ensuring seamless integration, deployment, and management of AI Models, with an emphasis on automation and best practices in MLOps to improve efficiency and reliability. Additionally, you will lead teams through the AI project lifecycle, fostering collaboration between technical teams and business stakeholders. You will also evaluate and mitigate risks associated with ML/AI deployments, promote ethical AI practices, and drive innovation.


Competencies & Skills Needed:

  • Proficiently develops and implements generative AI models, including content creation, data synthesis, and augmentative technologies like GPT, DALL·E, etc. Applies these models effectively to address intricate business challenges and foster innovation.
  • Exhibits advanced proficiency in MLOps practices, adept at designing, constructing, and overseeing automated ML pipelines. Ensures efficient deployment, monitoring, and maintenance of AI models in production environments.
  • Deals with Ambiguity - Demonstrates resilience in ambiguous situations by operating effectively despite uncertainty or lack of clarity. Makes informed decisions and takes action even in the absence of complete information. Approaches challenges with a constructive mindset, addressing problems without clear solutions or outcomes.
  • Proficient in utilizing advanced analytics methods for predictive modeling, segmentation, and deriving customer insights.
  • Demonstrated leadership abilities, encompassing guiding teams in adopting best practices throughout AI development and deployment processes.
  • Communicates Effectively -  Strong communication and interpersonal abilities, adept at conveying complex AI concepts and highlighting the significance of generative AI and MLOps initiatives to diverse audiences, including both technical and non-technical stakeholders.
  • Recognizes and comprehends ethical considerations and potential biases in AI, demonstrating proficiency in implementing strategies for the responsible use of AI.


What You’ll Do and Impact: 

  • This is a leadership role with direct reports. You will be responsible for managing a team and growth and development of partners you lead.
  • Analyze business problems, validate requirements, ensure full understanding of request scope, and translate business issues into data science problem statements.
  • Develop and maintain Machine Learning (ML) and AI solutions using programming platforms such as Spark/Scala, R, Python, and utilize big data/cloud solutions like AWS, Azure, etc.
  • Deploy AI solutions, including machine vision, natural language processing, voice recognition, etc., in cloud-based production environments using ML engineering frameworks, processes, and tools across various cloud platforms.
  • Apply econometric approaches such as zero-sum games, multi-market models, optimization, etc. algorithmically to solve business models.
  • Construct data pipelines and utilize appropriate database technologies to support AI/ML implementations. This includes troubleshooting problems, retraining models, and analyzing and updating data pipelines using tools like Kafka, Storm, MS SQL Server, Neo4j, HDFS, Redshift, S3, etc.
  • Conduct comprehensive data analysis and validate solutions using SQL querying languages and a thorough understanding of Direct Supply data structures and related external data sets.
  • Develop presentations, reports, and visualizations for business stakeholders using tools like Rmarkdown, shiny server, bokeh, matplotlib, ggplot, etc.
  • Mentor junior team members, interns, university researchers, etc., to help them understand how to build AI solutions within the Direct Supply context.
  • Collaborate with cross-functional partners, including Business Analysts, Engineers, and Data Scientists, to design experiments and implement scalable solutions.
  • Manage multiple projects and ensure timely completion of assigned work.
  • Utilize open source or off-the-shelf Generative AI models to create Minimum Viable Products (MVPs).



  • Masters and/or Ph.D. in Computational Science/Computer Science/Software Engineering Mathematics/Statistics/Economics/Healthcare Informatics/Business or 3 + years of industry experience in quantitative roles. 
  • 2-4+ years of experience working in data driven consultation roles such as Business Intelligence reporting, Advanced Analytics, AI/ML etc.
  • 3-5+ years of in-depth experience in programming tools like R, MATLAB, Python and database technology like SQL Server, MongoDB or Neo4j.
  • 2-3+ years of experience deploying AI/ML solutions using ML Engineering framework/process/tools in cloud preferably AWS & Azure.
  • 2+ years of experience with data visualization tools like Tableau, Shiny etc.
  • 2+ years of experience or comparable educational exposure using statistical learning approaches such as dimension reduction, sampling, cross validation, support vector machines, generalized linear models. 
  • Knowledge of version control, continuous integration/continuous deployment (CI/CD) practices, and cloud technologies essential for scalable and reliable AI solutions.
  • Deep knowledge in natural language processing (NLP) and the ability to leverage NLP for understanding, generating, and interpreting human language in a business context. 


Additional Items of Interest:

  • Previous experience coordinating projects, understanding requirements, creating milestones, and managing resources to obtain a desired result.
  • Experience in implementing solutions on cloud platforms like AWS, Azure, Google Cloud etc.
  • Experience with Generative AI tech stack.