Join a high-impact team as a Data Scientist where you will leverage statistical thinking, rigorous experimentation, and machine learning to solve complex business problems. This remote role offers the opportunity to partner with cross-functional leadership to turn ambiguous data into actionable strategic insights.
About the role
We are seeking a versatile and intellectually curious Data Scientist to join our team and drive value across an industry-agnostic landscape. In this role, you will act as a bridge between raw data and strategic decision-making, using your expertise to navigate complex datasets and extract meaningful patterns. You will be responsible for the entire lifecycle of data projects, from initial hypothesis generation and data cleaning to the deployment and monitoring of sophisticated models. This is an environment where your analytical rigor will directly influence the trajectory of our product and operations.
As a core member of our data organization, you will work closely with product managers, operations leads, and executive leadership to frame ambiguous business questions into testable experiments. You will not just be running scripts; you will be expected to think critically about the underlying business logic and the statistical validity of your findings. Whether you are identifying drivers of user behavior or optimizing internal workflows, your work will be grounded in a commitment to data quality and scientific integrity.
Communication is a cornerstone of this position. You must be able to translate complex statistical concepts into compelling narratives for non-technical stakeholders while maintaining the technical depth required to collaborate with engineering and data science peers. You will be expected to present your findings clearly, highlighting both the opportunities and the limitations of the data. By fostering a culture of data-driven transparency, you will help the organization make informed bets on its future.
The ideal candidate thrives in a remote-first environment and possesses a high degree of autonomy. You are someone who stays current with the latest advancements in the field but remains focused on applying the right tool for the specific problem at hand. We value practitioners who are as comfortable writing production-ready code as they are performing deep-dive exploratory analyses. Your contributions will ensure that our models remain performant, our experiments remain unbiased, and our business remains competitive.
Responsibilities
- Develop and deploy predictive models and statistical analyses to address high-impact business challenges.
- Define clear hypotheses and design rigorous experiments to validate product and operational assumptions.
- Evaluate and ensure data quality and integrity across various internal and external data sources.
- Communicate complex analytical findings to both technical peers and non-technical executive audiences.
- Partner closely with product, operations, and leadership teams to identify and prioritize growth opportunities.
- Monitor and maintain model performance over time to ensure continued accuracy and business relevance.
- Frame ambiguous business questions into structured analytical frameworks and actionable project roadmaps.
- Collaborate with engineering teams to integrate data science solutions into existing workflows and products.
Requirements
- Professional experience applying statistical thinking and analytical problem solving to real-world data.
- Proficiency in programming for data analysis using either Python or R.
- Advanced knowledge of SQL for data extraction, transformation, and manipulation.
- Demonstrated ability to create clear and impactful data visualizations to communicate trends.
- Proven track record of framing and solving ambiguous business questions with data-driven insights.
- Experience working with large-scale datasets and maintaining high standards for data quality.
- Strong communication skills with the ability to influence stakeholders at various levels of the organization.
- Legal authorization to work in the United States and ability to work effectively in a remote environment.
Preferred Qualifications
- Hands-on experience with machine learning techniques and production model deployment.
- Expertise in causal inference and advanced experimentation methodologies.
- Experience with Natural Language Processing (NLP) or time-series forecasting.
- Background in building and maintaining automated data pipelines and monitoring systems.
- Ability to contribute to the development of internal tools and best practices for the data science team.
Compensation
$105,000 – $165,000
Ready to apply?
Takes about three minutes.