Data Analyst Jobs At Numerator | Work From Home

Qualifications

• BS in Analytics, Mathematics, Statistics, Computer Science, Economics, Physics, or other behavioral and/or equivalent quantitative science
• Exceptional stakeholder skills; previous experience with stakeholder management is a plus
• Business intelligence or comparable analytic experience, including proficiency with BI tools such as Tableau, Looker, or Power BI.
• 2+ years of SQL experience with demonstrated advanced capabilities (Transactions and DDL, table self joins, Multipass SQL).
• Proven ability to: work in a team environment, produce results independently, solve complex problems, exhibit strong judgment, lead and manage in a fluid work environment
• Ideal: Knowledge of the software development life-cycle and the role of product in it.

Job Description:

Numerator is looking for a Data Science Analyst to join our growing Data Business Operations team. This is a unique opportunity where you will get a chance to work with an established and rapidly evolving platform that handles millions of requests and massive amounts of events, and other data.

In this position, you will be responsible for taking on new initiatives to automate, enhance, maintain, and scale services in a rapidly-scaling environment.

This Data Science Analyst position is a data quality oriented role that creates value and drives impact across the Product organization. The role is cross-functional by nature and is responsible for investigating pressing data issues surfaced by both internal and external clients and identifying the root cause so that we can collaboratively move towards a solution.

The ideal candidate has analytical experience, with an understanding of data transformations and data queries.

Roles & Responsibilities:

Forensic Data Analysis:

• Isolate underlying root causes of data integrity issues across product and platform
• Communicate technical findings to our non-technical consultants in an approachable, understandable manner
• Coordinate with engineers and technical team members to resolve bugs and creatively resolve root causes
• Work closely with panel science team to coordinate product-side fixes arising from data science design

Internal Product Development:

• Partner with Product and Engineering team members on complex data projects
• Identify commonalities among root cause and develop efficiency-building products to streamline forensic data analysis to isolate bugs more quickly
• Present developed products to first and second tier stakeholders
• Transfer ownership of complex projects from data scientists and handoff built projects to more junior team members