Role Snapshot
Senior Data Scientist role at ParentSquare, a rapidly growing edtech company serving 22+ million students. You'll deliver data-driven solutions that directly impact business decisions across Finance, Customer Success, and Product teams.
Key Responsibilities: Partner with cross-functional teams to understand data needs and deliver impactful analyses; build and deploy data-powered tools, automations, and dashboards; establish meaningful success metrics and monitor KPIs; balance pragmatic solutions with rigorous approaches while communicating tradeoffs to stakeholders; champion data adoption through documentation and training.
Skills & Tools: Fluency in Python and SQL with full analytics stack experience; strong foundation in statistical methods and machine learning algorithms (regression, classification); excellent communication and stakeholder management abilities; experience with LLMs and AI tools for analytics is a bonus.
Qualifications: 5+ years of experience in data science, analytics, or related quantitative field in high-growth SaaS/technology companies; Bachelor's degree in Statistics, Mathematics, Computer Science, or equivalent practical experience.
Location: Remote - Remote (United States)
Compensation: $143K–$175K/yr
Job Description
- Partner with Teams: Work directly with departments like Finance, Customer Success, and Product to understand their data needs, be their thought partner and deliver impactful solutions.
- Build and Deploy Solutions: Prototype and launch data-powered tools and automations, both for our customers and for the company.
- Define and Track What Matters: Help teams establish meaningful success metrics and build data products that report to monitor them.
- Balance Speed and Rigor: Recognize when to move fast with a pragmatic solution and when to invest in building the right system - and communicate those tradeoffs clearly to stakeholders.
- Champion Data Adoption: Create clear documentation, lead training sessions, and act as the internal expert to help teams more effectively use data tools within their workflows.
- Raise the Bar: Contribute to and evolve data science standards and practices across the team.
- 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
- Experience with LLMs and other AI tools for analytics is a bonus!
- Proven success working in a high-growth SaaS or technology company
- Fluency in scripting languages like Python and data querying languages like SQL
- Experience working in analytics platforms (we use AWS tools like Sagemaker and QuickSuite)
- Experience with a variety of machine learning algorithms, such as regression, gradient boosted trees, and topic modeling
- Experience understanding and delivering on stakeholder needs, whether through an adhoc analysis or a company-level dashboard
- Experience with LLMs and other AI tools for analytics is a bonus
- Employer-paid health insurance (including dependent coverage)
- An employer-matched 401K retirement savings program from day 1
- Paid Parental Leave
- Stock options
- Health + wellness reimbursements
- PTO that increases each year
- 15 paid holidays, including your birthday!
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