Data Analytics & Data Science Intern — Spring & Summer 2027
Simbe
- Pay
- $35 to $40
- an hour
- Location
- San Francisco, CA
- Work style
- Remote only
- Job type
- Internship
- Posted
- Oct 14
- 10 days ago
Career path
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About the company
Simbe
Retail · 51 to 200 employees
Simbe is building the AI-powered operating system for physical retail. Our autonomous robots and multimodal data collection systems turn complex, constantly changing stores into accurate, actionable intelligence for leading retailers around the world. Simbe combines robotics, computer vision, machine learning, data infrastructure, and analytics to help retailers improve shelf availability, inventory accuracy, store execution, and operational decision-making.
What you'll do
- Own and contribute to a scoped project aligned with the Data Science & Analytics team’s priorities during your internship.
- Write and maintain SQL and Python used 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 your project, approach, results, and key learnings at the end of the program.
What you need
- Currently pursuing a BS, MS, or PhD in Computer Science, Data Science, Statistics, Analytics, Applied Mathematics, Engineering, or a related technical field.
- We primarily target students in their final year of study 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.
- Experience with BigQuery, Google Cloud Platform, or another cloud data warehouse/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.
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