Data Analytics Manager
GongAbout the role
Gong transforms revenue organizations by harnessing customer interactions to increase business efficiency, improve decision-making and accelerate revenue growth. The Revenue Intelligence Platform uses proprietary artificial intelligence technology to enable teams to capture, understand and act on all customer interactions in a single, integrated platform. More than 4,000 companies around the world rely on Gong to support their go-to-market strategies and grow revenue efficiently. For more information, visit www.gong.io.
As a member of GTM Analytics and Data Science team, you’ll enable our Sales and RevOps teams with the data and insights they need to perform at their best. This includes managing our core reporting suite, compiling insights for quarterly business reviews, supporting forecasts, and measuring and reporting on performance against targets.
In addition to running these operations in their current state, you’ll own the research necessary to make them more effective as the company grows. Gong provides a very unique, rich dataset that will allow us to go beyond standard Sales analytics with conversation transcripts, Smart Trackers, and embedded AI.
RESPONSIBILITIES
- Work with stakeholders to create data solutions for business problems
- Build and maintain data and insights to support the sales operating rhythm (scorecards, forecast reports, quarterly business reviews, etc.)
- Use statistics and data science to optimize sales and management behavior (E.G., find milestones that new reps need to hit in their first six months in order to have long-term success)
- Use standard data tools (Snowflake, DBT, Tableau, Python) to build data pipelines, visualizations, and production ML models
- Communicate insights to business owners in concise, non-technical language
- Build lightweight data applications using Python/Javascript (E.G. a discounting calculator that identifies similar deals and recommends a pricing strategy)
QUALIFICATIONS
- 6+ years of experience in a Data Science or Analytics role
- Bachelors level in a quantitative field such as physical sciences, engineering, mathematics, or economics
- Technical Skill: Advanced SQL (Snowflake or Redshift preferred), Tableau, data wrangling in Python (data modeling in DBT is a plus)
- Data Knowledge: Becoming an expert in our internal data. Knowing exactly what we have at our disposal in order to build effective data tools and run effective analyses.
- Business Acumen: Understanding the SaaS business model, the Revenue Intelligence Market, and how we can apply our data to be successful as a Sales organization (Experience in SaaS is a plus)
- Curiosity & Creativity: Being curious enough to learn about our stakeholders’ needs and creative enough to connect the dots
- Ownership: Working toward impact, not just checking boxes, and occasionally going outside your usual responsibilities to make sure our work makes a difference (E.G. recording training videos, partnering with product to contribute to Gong’s functionality)
- Team Player: In order to be successful, we partner with several Finance and GTM functions. We need to be easy to work with in order for our work to have tangible value.
PERKS & BENEFITS
- We offer Gongsters a variety of medical, dental, and vision plans, designed to fit you and your family’s needs.
- Wellbeing Fund - flexible wellness stipend to support a healthy lifestyle.
- Mental Health benefits with covered therapy and coaching.
- 401(k) program to help you invest in your future.
- Education & learning stipend for personal growth and development.
- Flexible vacation time to promote a healthy work-life blend.
- Paid parental leave to support you and your family.
- Company-wide recharge days each quarter.
- Work from home stipend to help you succeed in a remote environment.
The annual salary hiring range for this position is $133,500 - $157,000 USD.
Compensation is based on factors unique to each candidate, including, but not limited to, job-related skills, qualification, education, experience, and location. At Gong, we have a location-based compensation structure, which means there may be a different range for candidates in other locations. The total compensation package for this position, in add
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