Senior Manager, Predictive Customer Engagement

Bristol Myers Squibb • Princeton, NJ

1d • Hybrid

About The Position

In support of Commercialization Strategy, the Sr. Manager of US Predictive Customer Engagement team develops and delivers analytical assessment, solution design and modeling capability relating to US customer experience and engagement across the portfolio, to drive competitive advantage and analytically informed decision making

Requirements

• BA/BS required (quantitative area of study preferred)
• Minimum of 3 years of experience
• Proficiency in Python/R and SQL
• Hands on experience with designing and deploying machine learning models using Scikit-Learn, Tensorflow, Pytorch, etc
• Experience with Git
• Experience with cloud based environments (AWS, Azure, etc)
• Experience with MLOps

Nice To Haves

• MBA/other graduate degree preferred and contribute to required years of experience

Responsibilities

• Hands-on data scientist or machine learning engineer that will be expected to ideate, design, develop, model and deploy advanced solutions
• Hands-on use of cutting-edge analytics and machine learning to understand and predict next best actions to improve US based customer experience and engagement using a variety of data sources to drive effectiveness of commercial tactics
• Build and own predictive machine learning based solutions for US Commercialization to enable better understanding, experience and engagement of our customers
• Employs disruptive thinking to improve value to the business and our US based customers through deepened market understanding, streamlined business engagement and practically applied, data driven analytics
• Use a sound mix of market knowledge, brand strategy and machine learning capabilities to build and enhance the quality of our predictive models
• Be able to translate the complexity of the machine learning models in business language to make the insights understood better and drive the use of these models further
• Partners with broader Commercialization Data Science & AI Predictive Solutions organization to provide guidance on how advanced analytics and machine learning can be leveraged to solve ad-hoc non-commercialization needs
• Partners with broader Commercialization Data Science & AI Predictive Solutions organization to monitor the external, Commercialization Analytics landscape, identifying and applying new capabilities in support of continuous BIA evolution and business performance

Benefits

• Medical, pharmacy, dental, and vision care.
• Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
• 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
• Paid Time Off US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
• Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
• Based on eligibility, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees