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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** TARRO PROFESSIONAL INC - **Location:** San Mateo, CA, United States - **Experience:** Experienced - **Salary:** $180,000.0 - $250,000.0 - **Contract:** Permanent contract - **Skills:** Airflow, Data Analysis, Unit Testing, Cloud Database, Cluster Analysis, Code Review, Continuous Integration, Information Engineering, Extract Transform Load (ETL), JSON, Python (Programming Language), Operational Data Store, Management of Software Versions, Workflow Management Systems, Data Processing, Sql Optimization, Snowflake, Prompt Engineering, Containerization, Information Technology, Low Latency, Power Analysis (Cryptography), Machine Learning Operations, Software Version Control, Docker, Web Api, Programming Languages - **Published:** September 4, 2026 - **Apply:** https://startup.jobs/data-scientist-tarro-7219656 ## About the Role 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., * 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, * 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. ## Description * 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 ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) - [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Dev Digest 120 - Apple and peers](https://www.wearedevelopers.com/magazine/455-dev-digest-120-apple-and-peers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)