Data Scientist

Do you want to empower organizations to build smarter compensation strategies while ensuring fair pay for all employees?

Syndio is a Series C technology company leveraging advanced technology and responsible AI to accelerate decision-making, streamline compliance, and democratize insights for consistent, equitable compensation practices at scale. Backed by $83M in investments from Bessemer Venture Partners, Voyager Capital, and Emerson Collective, we are expanding our team and products to help companies align their rewards strategies with their business goals.

Our customers are our greatest asset. Syndio partners with many of the world’s most recognized and respected enterprises, helping them implement leading-edge compensation solutions with expert guidance. We analyze pay for over 10 million employees across dozens of countries, ensuring fair, defensible rewards that drive better business outcomes.

Join us in our mission to eradicate workplace inequities and help companies create workplaces where every employee is valued for who they are and the impact they make.

We’re looking for a Data Scientist to join our growing data team and help transform raw, messy datasets into structured, useful data products that drive both internal insights and customer-facing features.

You’ll work closely with data engineers, product managers, and other stakeholders to improve the quality, consistency, and usability of our data—primarily in our warehouse (BigQuery). You’ll help design and implement data cleaning and transformation pipelines, define canonical datasets, and explore creative approaches to scaling how we prepare and deliver insights.

This is a great role for someone who enjoys working across messy real-world data, is comfortable collaborating cross-functionally, and wants to see their work show up directly in product and in thought leadership.

• Design and implement processes for cleaning, transforming, and enriching structured data in BigQuery.
• Create and maintain curated datasets that power dashboards, analytics, and in-product experiences.
• Partner with domain experts, engineers, analysts, and product managers to understand data needs and shape solutions that work at scale.
• Apply statistical, rules-based, or ML-driven methods to improve data quality and automate transformation where possible.
• Build new product features that leverage our data, such as recommendations models and data insights 
• Identify and address inconsistencies, ambiguities, and edge cases in compensation and HR datasets.
• Contribute to internal data standards, documentation, and data catalog efforts.
• Support downstream product and integration work by ensuring data is reliable and well-defined.

• Experience in data science, analytics engineering, or a related field, preference for production environments 
• Strong proficiency in SQL and Python, particularly for data wrangling and transformation.
• Experience working with large, complex datasets in a modern data warehouse (BigQuery a strong plus).
• Comfortable exploring imperfect data, identifying anomalies, and proposing solutions.
• Skilled at collaborating with both technical and non-technical partners to shape data solutions.
• Curious and creative—you’re excited to try new approaches to make data more useful.
• Familiarity with compensation or HR data is a plus
• Interest in supporting future use cases in product integrations or AI-enhanced data workflows.

At Syndio, we're building a diverse team that values candor, curiosity, and community. If you share these values and are interested in joining us, we'd love to talk with you even if you don't 100% meet the "about you" listed here. We don't expect anyone to have all the answers, as long as you're willing to learn and grow with us.

Employees joining the Syndio team at this early stage of growth will impact this critical social issue and support a growing customer base (including Nordstrom, General Mills, Match Group, and others) to take tangible action on workplace fairness. 

Syndio is an Equal Opportunity Employer. We are building an inclusive and collaborative workplace as we grow, and we welcome team members regardless of gender/identity, sexual orientation, race or cultural background, religion, physical disability and age.