Product operation manager

NPS Prism

17d•Hybrid

About The Position

NPS Prism is a market-leading, cloud-based CX benchmarking and operational improvement platform owned by Bain & Company. NPS Prism provides its customers with actionable insights and analysis that guide the creation of game-changing customer experiences. Based on rock-solid sampling, research, and analytic methodology, it lets customers see how they compare to their competitors on overall NPS®, and on every step of the customer journey. Launched in 2019, NPS Prism has rapidly grown to a team of over 200, serving dozens of clients around the world. While NPS Prism is its own company, NPS Prism is 100% owned by Bain & Company, one of the top management consulting firms in the world and a company consistently recognized as one of the world’s best places to work. We believe that diversity, inclusion, and collaboration are key to building extraordinary teams. We hire people with exceptional talents, abilities, and potential, then create an environment where you can become the best version of yourself and thrive professionally and personally. NPS Prism has experienced tremendous growth as a standalone software and data business over the past few years and is making the leap from being a consulting-led business to a technology-led business. Given that shift, we are looking to build our team with world-class team members to help drive business growth to its full potential in this next phase. This is a great opportunity to help build the largest startup owned by Bain & Company and take NPS Prism into the future.

Requirements

Graduate/post graduate from top-tier institute or have pursued a statistical/analytical course from a tier 1 university
2+ years of experience in areas related to Data Management, Business Intelligence or Business Analytics.
Hands-on experience in managing end-to-end customer surveys, data analysis and visualizations
Extensive hands-on experience with Tableau, with strong command of dashboard design, interactivity, and performance optimization
Proven experience using Alteryx for data prep, transformation, and validation at scale.
Proficient in applying statistical and data mining techniques to derive meaningful insights from customer feedback and survey data.
Comfort with SQL and Python (preferred), especially for data manipulation, automation, or analytics tasks
Proactive problem-solver with a strong sense of ownership and attention to detail.
Experience mentoring junior team members and contributing to collaborative team culture
Excellent interpersonal, written, and verbal communication skills
Comfort working in a hybrid or remote environment with distributed teams.
Demonstrates resilience and adaptability in navigating change and feedback.
Consistently seeks feedback and iterates to improve performance and team outcomes.

Nice To Haves

Concentration in a quantitative discipline such as Statistics, Mathematics, Engineering, Computer Science, Econometrics, Business Analytics, or Market Research.

Responsibilities

Independently owns the workstreams assigned to the individual and develops client ready visualization dashboards using tools like Tableau with minimum guidance
Works with multiple stakeholders, across instruments and workstreams to provide expertise in data management
Provides structured support to junior team members, including helping them understand tools, logic flows, and standard work practices.
Builds reusable capabilities and templates that improve team efficiency and scalability, ensuring that they are well documented and across service lines
Analyze the data using tools like SQL, Alteryx, and Databricks.
Design and execute new benchmarking survey instruments, including assessing data needs and designing the primary research surveys and sample specification
Respond to onshore team/client questions around the data and insights
Translates complex technical concepts such as screener logics, dashboard workflows, and research methodologies into clear explanations for internal teams and client facing discussions
Provide ongoing support for subscription customers, such as additional data cuts and responding to questions about the data/methodology with precision and speed
Support commercialization efforts, including conducting data-driven analysis for proposals, building custom outputs, and conducting product demos with prospective clients