Manager, Data Science

Job Description

Primary Responsibilities

·Drive product design and ensure consistent execution of product lifecycle processes from concept to launch, ensuring user-centric solutions·Define and monitor Product Success metrics and criteria at incremental product development phases, and product adoption·Facilitate cross-functional collaboration with engineering, marketing, and sales teams to align on product goals and roadmap planning for automation/improvements as per business needs·Effectively communicate progress, challenges, learning and success stories to key stakeholders·Lead creation of comprehensive playbook and training material to standardize and share SOPs with product development and other analytics teams·Gather user feedback to refine product features. Evaluate technical feasibility of new product features and enhancements. Ensure smooth handoff of product requirements to development teams·Lead creation of benchmark techniques being deployed across multiple product development strategies·Identify cutting-edge trends and best practices in the market to improve product positioning

Qualifications

Education & Work Experience Requirements:  

•Bachelor’s degree (in Engineering or related field, such as Computer Science, Data Science, Statistics, Business, etc.) with at least 6+ years relevant experience•Master’s degree (relevant field like Computer Science, Economics, Statistics, Mathematics, Operational Research) with 4+ years work experience•2+ Years of Product management or Software development experience

Skillset:  

Candidates must have -

•Strong proficiency in Python, SQL, and cloud-based environments (AWS, GCP, or Azure) is a must. Experience with APIs, microservices, and DevOps practices is a plus•Experience in Software Development and Engineering, and Analytics Delivery•Expertise in developing scalable, secure, and modular product architectures•Proficiency in designing & implementing data structure, pipeline & architecture•Hands-on experience with product roadmaps, Agile methodologies and backlog management, ensuring iterative and incremental product improvements•Strong problem solving, critical thinking, business analysis and quantitative skills•Story Boarding - Ability to effectively communicate proposals to key stakeholders•Understanding of end-to-end Pharma commercial landscape•Understanding of analytics tools like Tableau, PowerBI, Dataiku etc

Candidates are desired but not mandatory to have -  

•Experience with data science principles, machine learning (supervised and unsupervised) and GenAI algorithms, test-control analysis, A/B testing,  propensity score matching etc.•Experience working with healthcare, financial, or enterprise SaaS products•Experience with Marketing Mix Modeling and optimization with underlying concepts such as ad-stock, decay, interaction and halo effects etc.

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Merck & Co., Inc., Rahway, NJ, USA, also known as Merck Sharp & Dohme LLC, Rahway, NJ, USA, does not accept unsolicited assistance from search firms for employment opportunities. All CVs / resumes submitted by search firms to any employee at our company without a valid written search agreement in place for this position will be deemed the sole property of our company.  No fee will be paid in the event a candidate is hired by our company as a result of an agency referral where no pre-existing agreement is in place. Where agency agreements are in place, introductions are position specific. Please, no phone calls or emails. 

Employee Status:

Regular

Relocation:

VISA Sponsorship:

Travel Requirements:

Flexible Work Arrangements:

Not Applicable

Shift:

Valid Driving License:

Hazardous Material(s):

Required Skills:

Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Software Development, Stakeholder Relationship Management, Waterfall Model

Preferred Skills:

Job Posting End Date:

03/31/2025

*A job posting is effective until 11:59:59PM on the day BEFORE the listed job posting end date. Please ensure you apply to a job posting no later than the day BEFORE the job posting end date.