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Tarro

Data Scientist

Reposted 2 Months Ago
Hybrid
San Mateo, CA, USA
180K-250K Annually
Mid level
Hybrid
San Mateo, CA, USA
180K-250K Annually
Mid level
Design, develop, and deploy end-to-end data science pipelines and predictive models. Collaborate with product, engineering, and business teams to run experiments, implement MLops best practices (CI/CD, versioning, monitoring), and deliver scalable solutions (including LLM/RAG workflows) that improve restaurant operations and business outcomes.
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About Tarro

Our vision

Tarro is building the future of restaurant infrastructure. The U.S. restaurant industry is a trillion-dollar market, but it remains relatively underserved by technology. Running a restaurant comes with a never-ending list of operational work, and many owners spend most of their day on what they have to do rather than what they want to do. We envision a future where they can delegate that work to Tarro and focus on what they love doing.

Restaurant owners want more orders, better margins, and fewer operational headaches. Giving them software is only part of the answer. Our ecosystem brings phone ordering, online ordering, delivery, point of sale, payments, and marketing into one vertically integrated operation. We combine software, AI, and human operations so independent restaurants can hand that work to us end to end.

Using Tarro should feel like having experienced operators, engineers, and marketers working for your restaurant. Our job is to turn that expertise into services owners can rely on, without having to build those teams themselves.

Our traction

Thousands of restaurants have entrusted Tarro with their success. Since 2020, we’ve processed close to $3 billion in restaurant orders, helped those restaurants serve more than 20 million consumers, and taken an estimated 3 million hours of work off their teams’ hands. And we’re still early in our journey.

Our team

We’re a lean team with top talent from OpenAI, Meta, Google, Tesla, Square, Stripe, Shopify, and Citadel. We’re scrappy builders who love to roll up our sleeves and get into the details of improving a restaurant’s operations. Many of us regularly work in restaurants to experience firsthand what our users deal with.

We move quickly, keep process light, and expect high standards of craft. Our leaders stay hands-on, and our teams have the autonomy to make decisions and the responsibility to see them through.

At Tarro, product judgment and technical execution belong together. You’ll be trusted to understand the restaurant’s problem, decide how to solve it, and carry the solution through to something people use every day. If you want to build products restaurant owners depend on, we’d love to work with you.

What we're looking for:

We are looking to hire a Data Scientist to drive impactful insights and build data-driven solutions across multiple Tarro product areas. In this role, you’ll analyze complex datasets, develop predictive models, and collaborate closely with product, engineering, operations and a variety of stakeholders. You’ll own end-to-end data initiatives, deploy models into production, and play a critical role in shaping Tarro’s growth and evolution. As a key member of our growing team, you’ll move fast, experiment often, and wear many hats to uncover patterns, optimize decision-making, and solve high-impact business challenges.

What you will accomplish:
  • You will be responsible for owning entire data science model pipelines, from development to support

  • You will help make key decisions on the technologies and tools we use as we scale

  • You will write high quality code for all parts of our data science pipelines.

  • You will work closely with Marketing, Sales, Customer Success, Product and other functions to define and execute on data diagnosis, prediction, prescriptive and experimentation requirements

  • You will create scalable data science models following software and data engineering practices like versioning, CI/CD, workflow orchestration, data ops and ml ops

  • You will implement rigorous code reviews and testing guidelines to ensure that we have a high quality data science products

  • You will create and improve our data science CI/CD pipeline to enable high developer velocity

  • You will help in improving the life of independent restaurant owners and ultimately their customers

About you:
  • You have Bachelors in Computer Science or Engineering, Statistics, or equivalent experience.

  • You have 3+ years of ELT/ETL, data exploration, transformation and building production models.

  • You have 3+ years working with cloud databases, such as Snowflake, Redshift or similar

  • Practical experience with statistical testing (p/t/z tests, power analysis), time series, regression/classification, clustering, and NLP.

  • You have experience with programming languages such as Python and its usage for data processing, making API calls along with Advanced SQL

  • You have built with at least one of OpenAI/Anthropic/Google/OSS (Llama/Mistral), using embeddings, RAG (vector DB + hybrid search + re-ranking), prompt engineering, function/tool calling, JSON-schema outputs, and evaluation frameworks (e.g., prompt/unit tests, hallucination checks).

  • You have exposure to MLflow or equivalent for experiment tracking/model registry; data & model versioning; orchestration (Dagster/Airflow); containerization (Docker) and monitoring (latency, cost, quality)

  • You have exceptional product sense, communication and bias to ship

Bonus Points:
  • You have experience with dbt, Dagster, MLflow/DVC, Weights & Biases, or Feast/feature stores.

  • You are obsessed with data and patterns to solve business problems.

  • You will be jumping in deep into a new territory for the business, and you have a strong hunger to learn along with us.

  • You got Restaurant tech or marketplace/logistics experience; you’re customer-obsessed and love turning noisy operational data into outcomes.

HQ

Tarro San Francisco, California, USA Office

San Francisco, CA, United States

Tarro Menlo Park, California, USA Office

Menlo Park, CA, United States

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