Fast Facts
As the Lead Data Scientist at CodePath, you will spearhead the development of data infrastructure and initiatives, collaborating closely with diverse teams to provide impactful analytical solutions that advance computer science education.
Responsibilities: Lead data initiatives through strategy development, collaboration on data pipelines, and communication of analyses while implementing machine learning models to support business decision-making.
Skills: Proficiency in Python or R, cloud platforms, SQL, and data analysis tools, along with strong communication skills and experience in a startup environment.
Qualifications: 3+ years in data science or related field with a robust statistical and machine learning foundation and experience in deploying models.
Location: Remote, United States
Compensation: $135000 - $175000 / Annually
About the Role
Location: Remote, United States
Role Type: Full-Time
Reports To: CPO
Compensation: $135,000-$175,000 per year
We’re at a critical moment in our growth as an organization. 2025 is a year of incredible change at CodePath (check out our platform overview), and we’re looking for the right Lead Data Scientist to lead the charge on our small, skilled, and growing team.
As an early hire on our data team, you will collaborate with stakeholders across the organization to help build and maintain our next generation data infrastructure. In order to build out our capacity to use data effectively, we are looking for somebody resourceful with a problem solving mindset who is self-directed and able to work closely with data engineers, software developers, and business stakeholders. As our first data scientist, we expect you to design and execute effective data science initiatives, ML modeling, and BI analysis across everything we do, with a focus on what can be done with the organization's constraints and best interests in mind — which makes this a challenging, creative, and exciting technical position for an experienced data scientist.
The ideal candidate is an experienced Data Scientist who thrives in an early-stage startup environment, excels at independently performing analyses, and can lead our broader data strategy. The successful candidate will be inspired to deliver tactical internal insights, conduct influential research, and collaborate with external partners to transform computer science education and advance CodePath’s mission.
Key Activities
- Work with senior leaders to set and execute on a strategy for measuring and evaluating CodePath's impact
- Collaborate with data engineers and stakeholders to design, refine, and deploy data pipelines that feed models and analytics processes
- Create and maintain dashboards, visualizations, and reports that communicate complex analyses in a clear and actionable manner using tools like Tableau or other BI platforms
- Perform exploratory data analysis (EDA) to identify trends, patterns, and insights, and communicate findings to stakeholders
- Develop and implement models, including statistical and machine learning models, to support business decision-making
- Develop and maintain data processing workflows for model training, evaluation, and deployment
- Work closely with cross-functional teams to understand their data needs and translate business problems into analytical questions
- Develop and maintain documentation for data science workflows, models, and methodologies that help achieve business goals and support impact measurement
Qualifications
- 3+ years of relevant professional experience in data science, machine learning, or a related field
- Strong foundation in statistics, data analysis, and machine learning algorithms
- Proficient in Python or R, with experience in using libraries such as pandas, scikit-learn, TensorFlow, or PyTorch
- Experience working with cloud-based platforms such as Google Cloud, AWS, or Azure, especially in deploying machine learning models and querying data from data warehouses
- Substantial experience in SQL and working with large datasets, including data wrangling, cleaning, and transformation
- Familiarity with data engineering tools and concepts, and a strong understanding of how data models and pipelines support advanced analytics
- Excellent communication skills, with the ability to present complex analytical concepts to non-technical audiences in an understandable and engaging manner
- Experience with best practices for tools like Jupyter Notebooks, Git, and version control to ensure robust, reproducible analyses
- Proven ability to take projects from conceptualization to deployment, with an aptitude for problem-solving and troubleshooting
- Able to work productively under uncertainty, and deals with obstacles constructively with an eye on moving the organization towards goals
Additional Skills and Experience
- Proven ability to drive projects from conception to completion
- Aptitude for problem-solving and troubleshooting
- Excellent communication and collaboration skills
- Ability to work in a fast-paced, startup environment
- Proactive, independent, responsible attitude with the ability to learn quickly
