Senior Data Scientist

ParentSquare

5d•$143,000 - $175,000•Remote

About The Position

We are seeking a Senior Data Scientist who is naturally curious and relentlessly analytical, with a proven track record of delivering analysis that moves the needle. The ideal candidate knows when to build the right solution and when to just get it done, clearly communicating the call and tradeoffs. This role requires someone who leads with insight and lands on action, capable of bringing any audience along regardless of their technical background. A collaborative team player who elevates others and doesn't take themselves too seriously, with a sense of humor, is essential.

Requirements

Proven success working in a high-growth SaaS or technology company
5+ years of experience in data science, analytics, or a closely related quantitative field
Bachelor's degree in Statistics, Mathematics, Computer Science, or equivalent practical experience
Fluency in Python and SQL; comfortable working across the full analytics stack
Experience with statistical methods and ML algorithms (regression, classification, clustering, gradient boosting, topic modeling, etc.) - and the judgment to know when to use them
Hands-on experience with modern data and analytics platforms (dbt, Snowflake, Redshift, Tableau, Omni, QuickSight, or similar)
Demonstrated ability to deliver across the full range - from a quick ad hoc pull to a company-wide dashboard
Excellent communication skills; proven ability to translate technical findings for non-technical audiences
3+ years of experience in data science, data engineering, data analytics, or similar fields
Bachelor’s degree in a technical or quantitative field (e.g. Computer Science, Statistics, Mathematics) or equivalent practical experience

Nice To Haves

Experience with LLMs and other AI tools for analytics is a bonus!

Responsibilities

Partner with departments like Finance, Customer Success, and Product to understand their data needs, be their thought partner, and deliver impactful solutions.
Prototype and launch data-powered tools and automations for both customers and the company.
Help teams establish meaningful success metrics and build data products to monitor them.
Recognize when to move fast with a pragmatic solution and when to invest in building the right system, communicating these tradeoffs clearly to stakeholders.
Create clear documentation, lead training sessions, and act as the internal expert to help teams more effectively use data tools within their workflows.
Contribute to and evolve data science standards and practices across the team.