Job Title: Senior Data Scientist for Optimization
About Us:
CVS Health is a pioneering business transforming healthcare in the United States by making customer experiences more seamless, convenient and personalized.
Our Purpose:
We aim to deliver enhanced human-centric healthcare for a rapidly changing world. Our brand is anchored in heart, emphasizing how we deliver services is just as important as what we deliver.
Key Responsibilities:
* Data Science Application: Identify data science opportunities across CVS Health's retail business, focusing on promotions, personalization, and front store retail initiatives.
* Cross-Functional Collaboration: Partner with teams to develop technical and business approaches, fostering trust through Agile methodologies.
* Solution Development: Design and implement robust solutions using machine learning and statistical methods.
* Algorithm Development: Create, validate, and deploy algorithms and predictive models to analyze complex problems.
* Data Exploration: Analyze large volumes of structured and unstructured data to address complex business challenges.
* Advanced Analytics: Utilize advanced statistical techniques to derive insights informing strategic decision-making.
* Data Infrastructure: Develop and maintain data structures and pipelines to organize data.
* Continuous Learning: Stay updated on machine learning advancements to enhance capabilities.
Your Role:
Apply machine learning solutions to create efficient models driving actionable insights from extensive datasets. Collaborate with teams to identify impactful solutions to complex business problems.
Requirements:
* A PhD with 1+ years of experience, a Master's degree with 3+ years, or a Bachelor's degree with 5+ years of relevant experience in a STEM field.
* Proven experience analyzing complex problems and translating them into efficient data science algorithms.
* Expertise in optimization machine learning techniques, including supervised and unsupervised learning, forecasting, classification, natural language processing, and deep learning.
* Strong background in statistical learning, predictive and prescriptive analytics, and experience with big data technologies.
* Proficiency in Python and at least one object-oriented programming language, along with experience in machine learning frameworks.
* Familiarity with SQL, relational databases, and big data platforms.
* Domain knowledge in retail merchandising and experience managing multiple stakeholders while effectively communicating data-driven insights.