Data Analytics & Data Science Intern — Spring & Summer 2027
About The Position
Simbe is seeking a Data Analytics & Data Science Intern to join its Data Science & Analytics team for Spring and Summer 2027. The intern will work with production data generated by Simbe’s robot fleet, retail environments, and operational systems, turning it into reliable insights, analytical products, and internal tools. The role offers hands-on experience with data engineering, analytics, AI, and robotics, with an appropriately scoped project aligned with an active team initiative. Interns work full time from Simbe’s Burlingame, California headquarters as part of a structured cohort. Each intern has a hiring manager responsible for project scope, performance, and feedback, and a dedicated mentor separate from the hiring manager. The program includes structured midpoint feedback, opportunities to work with Simbe engineers and data practitioners, and a final project presentation. The project is selected closer to the start date based on active team priorities.
Requirements
- Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, Statistics, Analytics, Applied Mathematics, Engineering, or a related technical field; the company primarily targets students in their final year and will also consider strong juniors.
- Strong SQL skills and comfort working with structured datasets.
- Experience using Python for data analysis, scripting, or automation.
- Coursework or hands-on experience in data engineering, analytics, data science, databases, or a related area.
- Familiarity with Git or another source-control system.
- Ability to investigate data carefully, recognize when results do not make sense, and validate conclusions.
- Strong technical problem-solving skills and willingness to work through ambiguous or unfamiliar problems.
- Strong written and verbal communication skills.
Nice To Haves
- Experience with BigQuery, Google Cloud Platform, or another cloud data warehouse or platform.
- Familiarity with dbt or another SQL-based data transformation framework.
- Exposure to dimensional modeling concepts, including star schemas or Kimball-style modeling.
- Experience building dashboards or reports in Looker, Tableau, Power BI, or a similar BI tool.
- Familiarity with data pipelines, ETL/ELT, workflow orchestration, or tools such as Airflow.
- Experience with pandas, Jupyter notebooks, or other Python data tooling.
- Experience writing automated data tests, monitoring data quality, or documenting analytical models and metrics.
- Personal data, software, analytics, or AI projects outside of coursework.
- Previous internship, research, or project experience involving data engineering, analytics engineering, BI, or data science.
- Experience using AI-assisted coding, LLMs, or automation tools to accelerate analysis or software development, with good judgment around validating generated output.
- Interest in building conversational or natural-language interfaces over structured data.
Responsibilities
- Own and contribute to a scoped project aligned with the Data Science & Analytics team’s priorities.
- Write and maintain SQL and Python for data analysis, transformation, validation, or automation.
- Work with data in BigQuery and help transform raw information into trustworthy analytical datasets.
- Contribute to dbt models, tests, documentation, and other analytics engineering workflows.
- Support dimensional modeling and development of organized data marts for analytical and reporting use cases.
- Build or improve dashboards and reporting in tools such as Looker.
- Investigate data-quality issues, validate results, and help ensure metrics are accurate and reliable.
- Analyze fleet, service, store, or retail data and communicate useful findings to technical and non-technical stakeholders.
- Depending on team priorities, contribute to AI-assisted analytics prototypes or tools that make data easier to explore and understand.
- Collaborate with Data Science, Engineering, Product, Operations, and other teams to understand data requirements and business context.
- Communicate progress, technical decisions, challenges, and results throughout the internship.
- Present the project, approach, results, and key learnings at the end of the program.
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What This Job Offers
Job Type
Full-time
Career Level
Intern
Education Level
No Education Listed
