Join MSD as a Technical Product Manager - Advanced Data Analytics

Job Description

Our company's enterprise data and analytics function, "CDNA," tackles enterprise-wide data and analytics challenges with a customer-centric, product-driven approach. As an accelerator, CDNA covers the spectrum from data discovery and identification to data acquisition, integration, advanced analytics, consumption, insights, and cognitive capabilities. Our mission is to empower our business divisions to perform analytics at hype, velocity, and scale, driven by talented and passionate professionals.

This role will be part of CDNA’s “Advanced Analytics” function, providing strategic and technical leadership to deliver a range of product capabilities.

The Opportunity

Are you an innovative technical expert eager to make a significant impact in a data-centric organization within a large enterprise? Do you thrive in a dynamic environment where you can help build modular solutions and enable a fully integrated end-to-end customer journey? If so, we want you to leverage your technology skills to drive the success of our analytics products and services. Join us in our quest to create value-added, self-serve data and analytics products.

Key Responsibilities

• Collaborate with cross-functional teams, including data scientists, engineers, and stakeholders, to define and refine technical requirements for our products.
• Work closely with Product Managers to translate business requirements into actionable technical specifications, ensuring alignment between business and technical needs.
• Collaborate with engineering teams to estimate release timelines, ensure timely delivery of product updates, and plan/execute product development for optimal implementation.
• Define and prioritize features and enhancements based on technical feasibility, scalability, performance, and user experience.
• Integrate algorithms, models, and data pipelines into our platforms, ensuring smooth functioning of analytics capabilities.
• Coordinate with the enablement team to ensure proper operational coverage of products in alignment with adoption strategies.
• Conduct thorough testing and quality assurance to ensure the reliability, robustness, and accuracy of our platforms.
• Adhere to SDLC guidelines for each product release, ensuring efficient development and deployment practices.
• Conduct solution reviews and guide engineering teams in building optimal and reusable solutions.
• Identify and utilize collaborative opportunities with technical leads across different products for knowledge exchange.
• Stay updated with emerging technologies in data science, machine learning, and analytics, conducting proofs-of-concept to assess their potential value.

Required Qualifications

• Strong technical expertise in modern data and analytics technologies within the AWS ecosystem and on-premises.
• Extensive experience developing systems in cloud environments.
• In-depth understanding of data science, analytics principles, modeling concepts, and industrialization methods.
• Expert knowledge of the AWS cloud ecosystem, including storage, database, streaming, messaging, AI/ML, cognitive, and scalability services like EKS.
• Understanding of self-serve product-centric data analytics principles.
• Expert-level knowledge of Databricks, Dataiku, Posit, SageMaker, and similar platforms.
• Hands-on experience with MLOPs and DevOps technologies such as GitHub, Git CI/CD, and Jenkins, including model deployment automation.
• Excellent interpersonal and communication skills; adept at working with colleagues from diverse disciplines and articulating complex technical topics.
• Proven ability to execute consistently and effectively in a fast-paced environment.
• Strong organizational skills, with the ability to navigate a matrix environment and prioritize work efficiently.
• Strong product and customer centricity with a focus on business value.

What We Offer

• Exciting work within a global projects team and an international environment.
• Opportunities to learn and grow professionally within the company globally.
• Hybrid working model with flexible role patterns (e.g., 80% full-time in justified cases).
• Pension and health insurance contributions.
• Internal reward system plus referral program.
• 5 weeks annual leave, 5 sick days, 15 days of certified sick leave paid above statutory requirements, 40 paid hours for volunteering activities, and 12 weeks of parental contribution annually.
• Cafeteria for tax-free benefits including meal vouchers, sports, culture, health, and travel