Job Description
We are seeking a Data Scientist to support our Fortune 100 client, a global provider of healthcare and retail pharmacy services, in building industry-leading analytics, data, and technology platforms to help reimagine health care. This position will play a critical role within a cross-functional team, delivering powerful solutions.
This is a hands-on, mid-level Data Scientist role, requiring a combination of business/stakeholder consulting and data analysis (technical coding, including using machine learning methods).
The Details:
- Location: Hybrid in Manhattan, NYC (3 days per week onsite required)
- Duration: 15+ month consulting role with potential conversion to hire
- Benefits: We do offer benefits to our full-time consultants, including Health, Vision, Dental, 401K plan, Life Insurance, Pretax Commuter Benefits, and an incredibly supportive team cheering you on!
What you’ll do:
- Generate insights, build machine learning, deep learning and statistical predictive models and develop analytical approaches which form the foundation for driving patient engagement tactics aimed at improving medication adherence and patient experience.
- Deploy large scale machine learning and deep learning models in a production environment.
- Effectively collaborate with Data Engineering, IT, and other technical teams to onboard new data sources, create feature stores, and optimize/automate model development and deployment processes (Github, MLOps etc.).
- Perform data quality assessments, remediate or curate data as necessary, and perform data modeling.
- Write complex and efficient SQL code and leverage Exploratory Data Analysis techniques to develop insights from billions of transactional records at the Retail Pharmacy.
- Prepare communication material such as presentations and reports, collaborate effectively with business, marketing, trade and other stakeholders across the organization.
- Mentor peers and lead intern projects.
Qualifications
Required Qualifications:
- 3-5 years of hands-on experience in generating business insights, machine learning and deep learning frameworks
- Strong experience with deployment of machine learning and deep learning models in production
- Strong proficiency with Python and SQL, data quality assessment and data modeling
- Strong proficiency with Github and MLOps
Preferred Qualifications:
- Strong experience with cloud-based ML frameworks (either AWS, Azure or GCP)