Data Scientist Manager

Role Description

At Solace, data isn't just about understanding the past; it's about predicting the future and running the systems that operate our marketplace in real time. We're looking for a technical Data Science Manager to lead and grow our Data Science team.

In this role, you will manage and mentor a team of 4-6 data scientists, owning their growth and the team's roadmap end to end. Reporting to the VP of Data, you will be the connective tissue between Data Science and the rest of the business, working closely with Engineering, Analytics, Product, Marketing, and Operations to prioritize what the team works on and see it through to impact. Your team owns two distinct threads of work:

• Predictive analytics that keeps the business ahead of its own growth.
• Production machine learning that powers our core product.

At Solace, we hold managers to a high technical bar: you need to be credible enough with your team to go deep, not just manage from above.

What You'll Do

• Coach and Develop the Team:
  • Manage and mentor data scientists, giving them the feedback and growth opportunities to build stronger judgment and take on more ownership.
• Own the Roadmap:
  • Set and drive execution of the Data Science roadmap, acting as the intake point for cross-functional requests and making deliberate prioritization decisions.
• Build Cross-Functional Relationships:
  • Partner closely with leaders to ensure that data science is embedded in how decisions get made, not layered on after the fact.
• Drive Marketplace Forecasting:
  • Own the forecasts and targets that keep advocate capacity, funnel volume, and supply and demand aligned, giving the business clear numbers to plan and hire against.
• Own Production ML Systems:
  • Own the machine learning models that run inside our core product, including matching and quality scoring, from prototype through production.
• Establish Best Practices:
  • Set the standard for how data science gets done at Solace, including code review, experimentation design, model validation, and monitoring.

Qualifications

• 6+ Years of Data Science Experience:
  • Proven track record building and shipping predictive models and machine learning systems, ideally at a product-led tech startup or marketplace.
• 2+ Years of Management or Leadership Experience:
  • Direct experience managing, mentoring, or leading data scientists or a similar technical team.
• Deep Python, ML & SQL Fluency:
  • Fluent in Python, its data science ecosystem, and the advanced SQL needed to pull your own data from Snowflake. You can read, debug, and meaningfully critique your team's code and models.
• Production ML Experience:
  • You have taken models from notebook to production, with experience monitoring, detecting drift, and iterating on models running live.
• Statistical & Forecasting Expertise:
  • Strong background in statistics and time-series forecasting (e.g., ARIMA, Prophet).
• Experimentation Rigor:
  • Strong grounding in A/B testing and causal inference, with a track record of designing experiments that produce trustworthy results.
• Exceptional Communication:
  • You can translate complex modeling work into clear narratives for non-technical executives and cross-functional partners.
• Startup DNA:
  • You thrive in ambiguity, move with urgency, and are comfortable wearing multiple hats.

Bonus Points

• Marketplace Matching Experience:
  • Experience designing matching algorithms or ranking systems for multi-sided marketplaces.
• Healthcare Experience:
  • Experience working with healthcare or insurance claims data.
• MLOps Tooling:
  • Experience packaging, deploying, and monitoring models in production, including containerization (Docker), experiment tracking and model registries (e.g. MLflow, SageMaker), and CI/CD for model deployment.
• dbt & Engineering Skills:
  • Comfort reading or writing dbt models to understand data lineage.
• Advanced Degree:
  • Master's or PhD in Data Science, Statistics, Applied Math, or a related field.

Up for the Challenge?

We look forward to meeting you.

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