Product Analyst, B2B

The Data Science team focuses on helping drive business outcomes across Calm. The business problem comes first (what are we trying to solve?), and the analysis follows (how do we best solve this problem?). Sometimes the solution is straightforward and sometimes it is highly complex—we always rely on data to drive our solutions.

As a Product Analyst for Calm’s B2B business you will be responsible for data products and analyses to support both external B2B customers as well as internal product and go-to-market teams. You will help drive quality analytics practices end-to-end: From building tracking plans for new product features, to delivering analysis-backed recommendations to B2B business leaders. Your role will be critical to delivering the key data points and insights to decision makers, helping move the company forward.

We are hiring remote workers for this role in the San Francisco Bay Area, Los Angeles, New York City, or Minneapolis areas. At this time, only candidates in these locations will be considered.

• Produce ad-hoc analyses on data across various sources (e.g. event streams, salesforce, application data), translating results into actionable summaries and recommendations
• Build and maintain operational dashboards in BI tools to enable internal partners to answer their most common questions
• Engineer data models for our production pipeline, which feed into high visibility dashboards critical for stakeholder decision-making
• Partner with product managers and engineers to develop tracking plans to ensure high quality data is available for performance measurement and analysis
• Serve as a bridge between Calm’s B2B product and go-to-market teams. For example, tying operational initiatives (e.g. marketing campaigns) to product outcomes (e.g. new users) and vice-versa.

• Building a customer reporting dashboard to enable our Customer Success team to deliver trustworthy and insightful reports to our customers
• Supporting the end-to-end analytics needs for a new product launch: From ensuring required tracking is in place to presenting success metric readouts to product leadership
• Working closely with sales operations, finance and data engineering teams to build a company KPI dashboard for the B2B leadership team
• Partnering with Customer Success managers and data teams from B2B external customers to deliver high-value reporting products

• Experience working in a product analytics tool such as Amplitude, Mixpanel or Heap
• Prior experience and enthusiasm for building and maintaining data products in a BI tool (e.g. Tableau, Looker, Power BI)
• Experience building data models, preferably using dbt
• Ability to translate non-technical business requirements into technical solutions, and translate technical solutions to business outcomes
• Proven track record of building relationships and influencing others within and across immediate working groups
• Hands-on experience building data documentation and testing practices
• Comfortable being an early team member and navigating ambiguity
• Experience working with cloud based data warehouses like Google BigQuery, Redshift, or Snowflake

• Prior experience working with a subscription or B2B SaaS business

• 5 years of relevant experience
• 4+ years of experience in an Analyst or Data Science role
• Strong proficiency in SQL

Calm uses a geographic pay model that determines salaries based on the location where an employee lives. For this position, the base pay ranges across Calm’s pay tiers is as follows: $88,560 – $183,700. The base pay range represents the low and high end of Calm’s salary range for this position. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which include the successful candidate’s geographic location, skills, experience and other qualifications. Calm uses employee zip code to determine which pay range applies. This role is also eligible for equity + comprehensive benefits + 401k + flexible time off.

Please note that Calm may leverage artificial intelligence technology in the application review process.

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