Fast Facts

CodePath is seeking a Data Scientist to lead the development of their data infrastructure, collaborate with cross-functional teams, and drive data science initiatives as part of a growing team in a remote capacity.

Responsibilities: Key activities include designing and deploying data pipelines, creating dashboards and visualizations, performing exploratory data analysis, implementing machine learning models, and translating business problems into analytical questions.

Skills: Proficiency in Python or R, experience with cloud platforms, SQL expertise, strong foundation in statistics and data analysis, and familiarity with data engineering tools are required.

Qualifications: 2 to 5 years of relevant experience in data science or machine learning, strong statistical analysis background, and excellent communication skills.

Location: Remote, United States

Compensation: $120000 - $160000 / Annually

About the Role

Location: Remote, US

Duration: FTE

Reports To: CLO

Compensation: $120,000-$160,000 per year

We’re at a critical moment in our growth as an organization. 2024 is a year of incredible change at CodePath (check out our platform overview), and we’re looking for the right 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. We expect the new hire to design and execute effective data science initiatives, ML modeling, and BI analysis across everything we do — which makes this a challenging, creative, and exciting technical position for an experienced data scientist.

Key Activities

• 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

• 2 to 5 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

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