Fast Facts
CodePath is seeking a Data Scientist to lead data initiatives within a growing team, focusing on building data infrastructure and analyzing complex datasets to support business decision-making.
Responsibilities: Key responsibilities include collaborating with data engineers to design data pipelines, creating dashboards and reports, performing exploratory data analysis, developing machine learning models, and maintaining data workflows.
Skills: Required skills include proficiency in Python or R, strong foundational knowledge in statistics and machine learning, experience with cloud platforms, substantial SQL experience, and excellent communication skills.
Qualifications: Preferred qualifications include 2 to 5 years of experience in data science, familiarity with data engineering tools, and a proven ability to drive projects to completion.
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
