Lead Data Scientist
AI Summary
Leads the end-to-end development, validation, and deployment of large-scale predictive models and algorithms to inform strategic business decisions and market trend analysis.
About this role
At Compass, our mission is to help everyone find their place in the world. Founded in 2012, we’re revolutionizing the real estate industry with our end-to-end platform that empowers residential real estate agents to deliver exceptional service to seller and buyer clients.
About the Role:
We are seeking a highly skilled and motivated Lead Data Scientist to join our data science team. In this role, you will leverage your deep expertise in machine learning, statistical modeling, and data analysis to solve our most complex problems. You will set the standard for data science excellence, architect scalable solutions, and help define the long-term analytical strategy. You will partner with senior business stakeholders and engineering leaders to uncover insights, develop cutting-edge data-driven solutions, and drive initiatives that directly shape company-wide strategic planning, resource allocation, and product innovation.
Responsibilities:
- Lead the end-to-end development, validation, and deployment of large-scale predictive models and algorithms that inform strategic business decisions and market trend analysis.
- Design and execute rigorous data-driven research to analyze the impact of multi-faceted factors on business outcomes, tackling the organization’s most highly ambiguous and open-ended problems.
- Collaborate deeply with senior business stakeholders and engineering partners to identify strategic opportunities, translate overarching business goals into complex analytical frameworks, and deliver high-impact actionable insights.
- Synthesize and communicate highly complex methodologies, technical trade-offs, and strategic findings clearly to both C-level executives and technical audiences.
- Act as a technical mentor to other data scientists, fostering a culture of continuous learning, rigorous peer review, and adherence to state-of-the-art methodologies.
Qualifications:
- Master's degree or PhD in Computer Science, Statistics, Economics, Mathematics, or a related quantitative field.
- 5+ years of experience in data science with a proven track record of conceptualizing, leading, and delivering highly successful, end-to-end data science projects.
- Deep expertise in key data science domains (e.g., time-series forecasting, deep learning, causal inference).
- Extensive practical experience architecting solutions using a broad range of methodologies (e.g., prediction, segmentation, NLP).
- Demonstrated proficiency in Python and SQL for complex data manipulation, statistical analysis, and model development.
- Hands-on experience productionizing machine learning models and strong familiarity with MLOps concepts and workflows.
- Proven experience leading complex, cross-functional projects and applying advanced methodologies to solve ambiguous business problems.
- Strong advocate for clean code principles, software engineering best practices, and technical standards.
- Strong business acumen and strategic thinking, with a proven ability to understand the broader business context, evaluate tradeoffs, and align analytical projects with organizational goals.
- Experience mentoring and guiding junior team members, overseeing project quality, and investigating root causes of complex technical challenges.
- Exceptional communication and collaboration skills, with a proven ability to work effectively in a fast-paced, cross-functional environment.
- Experience in the Real Estate industry or other market-driven domains is a plus.
Compensation: The base pay range for this position is $175,500-195,000 annually; however, base pay offered may vary depending on job-related knowledge, skills, and experience. Bonuses and restricted stock units may be provided as part of the compensation package, in addition to a full range of benefits. Base pay is based on market location. Minimum wage for the position will always be met.
Perks that You Need to Know About:
Participation in our incentive programs (which may include eligible cash, equity, or commissions). Plus paid vacation, holidays, sick time, parental leave, and recharge leave; medical, tele-health, dental and vision benefits; 401(k) plan; flexible spending accounts (FSAs); commuter program; life and disability insurance; Maven (a support system for new parents); Carrot (fertility benefits); UrbanSitter (caregiver referral network); Employee Assistance Program; and pet insurance.
Skills
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