Product Manager, Data Analytics

San Francisco, CA, United States Posted 23 days ago

Logikcull’s mission is to democratize discovery. The costs and risks associated with complex data projects like e-discovery, responding to FOIA requests, and conducting internal investigations are skyrocketing as the amount of data increases. Logikcull is transforming these tasks so they can be completed in minutes, by anyone, anywhere. As a result, our customers--modern legal teams from solo attorneys to massive law firms, Fortune 500 companies, and leading non-profit organizations -- can find and use important information quickly so they can focus on their important work, like pursuing a better democracy or saving the Earth.

Who we are:

Logikcull.com is instant discovery for modern legal teams. Its secure, cloud-based solution helps law firms and organizations of all sizes solve the expensive, complex, and risky challenges associated with eDiscovery, internal investigations, and open records response. With Logikcull, you can start a discovery project in five seconds, from anywhere at any time on any device.

What we need:

Logikcull is a product-led growth company and we are in need of an Analytics PM to help us double in size again. This person will spearhead the data initiative at the company to plan, vet and purchase various aspects of the data infrastructure we will need including a data warehouse, visualization tooling and potentially other tools pertaining to ETL and BI that are required to drive our product forward. Additionally, we are looking for someone who loves data-mining for Product insights that help inform our roadmap as well as teach others at the company how to do the same. We need someone who is empathetic to the analytic needs of product owners, engineers, and designers, the right candidate has the ability to translate data requirements into usable, scalable data structures in a way everyone can understand.

What you'll be doing:
  • Reviewing and analyzing data to advise our product growth
  • Assess our current tools and systems, then advise on the aspects of data structure we need moving forward
  • Be an advisor to our team on how to think about and analyze data
  • Implement our Data warehouse, ETL and BI tools
  • Lay the foundation for any Machine Learning/Intelligence initiatives in the future
  • Provide regular updates for technical and non-technical stakeholders about dataset updates and necessary changes
  • Practice good data hygiene and implementation standards
  • Combine the voice and needs of the users and business requirements to create both high-level roadmaps and detailed delivery plans of features and capabilities based on the data
  • Use a metrics driven product development approach. Define success measures for roadmap items and demonstrate measurable impact on those success metrics
  • Mind melding with key stakeholders throughout the organization including Engineering, Design, Finance and the Exec teams on the product vision using data
  • Lead and collaborate on all business readiness activities including product testing, end user education, rollout, iteration and support
What we need from you:
  • 5+ years of experience working in a data driven role or Product Manager role
  • You love data and taking chaos and turning it into something actionable
  • Previous experience with analytics tools and understanding of the analytics landscape
  • Extensive experience running deep analysis of a data set
  • Ability to run SQL queries for common metrics such as funnel conversion, churn etc.
  • Enjoys the fast paced, ever changing landscape of a startup
  • Strong communication skills, both written and oral, and an ability to listen and understand root needs across many different business units
  • Well-established personal processes to handle multiple requests from varied stakeholders, in a way that maintains clear priority, adjusts when needed, and is always helpful and pleasant
  • Successful track record of building data products and capabilities
  • Highly analytical and collaborative qualities with strong technical, strategic and problem-solving skills
  • An understanding of the technical architecture of data and machine learning pipelines
  • High sense of ownership and a focus on building fast without sacrificing quality
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