Description & RequirementsBloomberg runs on data, and data drives the market. Our GDSI team is an integral part of driving our business through data-backed decision making for Bloomberg Media. Individuals on the team lead strategic analytics projects, from development and analysis to presentation, working alongside key decision makers across the Media business.
The GDSI team is looking for a Manager of Analytics with deep experience in subscription and digital product analytics, who can bring both strategic thinking and hands-on technical skills. You will partner closely with leaders across Subscriptions, Product, Marketing, and Editorial, while supporting additional business units including Commercial, Engineering, Research, Finance, and Strategy/Operations.
This highly visible, cross-functional role will require technical expertise in SQL and Python, strong analytical storytelling, and the ability to influence product and business strategy. As a senior individual contributor, you will independently lead complex analytical initiatives, help shape measurement and analytics strategy, and serve as a trusted analytical partner to stakeholders across Bloomberg Media.
This role will also optimize the use of advanced tools and methodologies such as machine learning, predictive analytics, and experimentation, helping us stay competitive by leveraging the latest analytical techniques. Think of this role as part strategist, part executioner, part business insights partner, and part data architect.
We'll trust you to:
- Perform advanced analysis across subscriber acquisition, conversion, engagement, retention, churn, lifecycle behavior, payments, product usage, content performance, and competitive performance.
- Lead complex, high-impact analytics projects focused on understanding subscriber behavior, evaluating product performance, and identifying opportunities to grow and strengthen Bloomberg Media's subscription business.
- Partner closely with Product and Subscription teams to define analytical questions, evaluate customer journeys and product experiences, and translate findings into actionable product and business recommendations.
- Collaborate with the Data Engineering team to provide high-quality data requirements for complex SQL or Python pipelines, ensuring a trusted source of truth for key Bloomberg metrics.
- Partner with Product, Subscriptions, Marketing, Data Engineering, and Finance teams to define KPIs, measurement frameworks, and performance reporting that connect customer and product behavior to business outcomes.
- Serve as a senior analytical resource for the GDSI team, providing technical and analytical guidance and helping unblock complex analytical challenges.
- Apply statistical methods, predictive modeling, experimentation, segmentation, and other advanced analytical techniques to solve complex subscription and product questions.
- Identify opportunities to leverage machine learning, predictive analytics, and automation to deepen our understanding of subscriber behavior and improve decision making.
- Monitor industry standards, market shifts, competitive dynamics, and emerging subscription and digital product trends to inform and advance our analytical capabilities.
- Identify new opportunities for leveraging data across Bloomberg's subscription and product ecosystem.
- Translate ambiguous business questions into structured analytical approaches, clearly articulating hypotheses, methodology, findings, and recommended actions.
- Clearly, consistently, and broadly communicate insights that inform subscription strategy, product vision, priorities, goals, and impact to leadership and across the organization.
You'll need to have:
- Bachelor's or Master's degree in a research-related or quantitative field such as computer science, statistics, mathematics, economics, or similar.
- 5+ years of hands-on experience in analytics or related fields, with a strong focus on subscription, consumer, or digital product analytics.
- Demonstrated technical expertise with SQL and Python, including experience writing complex queries and building scalable analysis pipelines.
- Familiarity with large-scale data platforms and data management or digital analytics tools such as BigQuery, Google Analytics, or similar technologies.
- Strong data visualization and analytical storytelling skills using tools such as Mode, Looker, Tableau, or similar platforms.
- Experience with B2C subscription products, including acquisition, conversion, engagement, retention, churn, lifecycle behavior, and payments.
- Strong experience with digital product analytics, including using behavioral data to understand customer journeys, product adoption, feature performance, and opportunities for growth.
- Strong background in statistics and advanced analytics, including predictive modeling, experimentation, segmentation, or related methods.
- Ability to independently own complex analytical initiatives from problem definition and methodology through analysis, recommendations, and communication.
- Ability to break down complex and ambiguous problems into structured, step-by-step analytical solutions.
- Highly effective communication and collaboration skills, with the ability to influence senior stakeholders and build strong partnerships across Product, Subscriptions, Marketing, Engineering, Finance, Editorial, and other cross-functional teams.
Salary Range = 70,000 - 95,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
