Data ML Ops Engineer
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Job Location:
San Francisco, CA - USA
Monthly Salary:
$ 170 - 220
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
What We Do
We provide savings on insurance premiums for commercial businesses that are leveraging modern technology on their worksites.
While we began with commercial construction were expanding into adjacent sectors including Energy Agriculture and Real Estate.
Our Investors
To date Shepherd has raised over $20M from leading investors including:
And several more.
Our Team
Were a team of technologists and insurance enthusiasts bridging the two worlds together. Check out our team page to meet some of us!
The Role
About You & the Role
You love building data pipelines that power real-world decisions especially in industries where accuracy and speed matter.
You thrive in fast-moving environments balancing short-term delivery (get the model live!) with long-term scalability (make the pipeline maintainable).
Youre adaptable and resourceful when a dataset is messy or an API is flaky you find creative ways to make it work.
Youll own data engineering across multiple initiatives building ingestion pipelines preprocessing frameworks and model registry integrations.
Youll work closely with leadership and technical leads partnering with actuaries data scientists and product managers to make pricing data self-serve and production-ready.
What Youll Do
Build pipelines and integrations ingest external data sources and structure them for pricing models.
Develop preprocessing frameworks ensure parity between training and production datasets across exposures claims and firmographics.
Enable model deployment at scale support the model registries so the actuarial team can push new models into production with minimal engineering lift.
Keep data clean and accessible design systems that handle structured semi-structured and event-based ingestion with speed accuracy and transparency.
Collaborate cross-functionally work with actuaries engineers and product managers to define requirements solve edge cases and keep models moving from prototype to production.
Youd be our dream candidate if
Youre a builder at heart with 4 years of experience as a Data Engineer ideally in SaaS fintech or insurtech building pipelines that serve ML/analytics products.
You make things happen experienced in deploying production-grade ETL wrangling messy data and supporting ML model deployment with tools such as Dagster/Airflow/Prefect and data warehouses (Redshift/Databricks/Snowflake) and maybe modeling libraries (statsmodels/scikit-learn/pytorch)
Youre a communicator and collaborator able to translate technical details (schema migrations data transformations) into clear decisions with non-technical stakeholders.
Bonus points for experience with MLflow/Sagemaker model registries insurance/actuarial datasets or prior startup/high-growth environments.
Benefits
Premium Healthcare
100% contribution to top-tier health dental and vision
Unlimited PTO
Flexibility to take the time off recharge and perform
Daily lunches dinners and snacks
We work together and enjoy meals together too
SF NYC or Dallas-Fort Worth Offices
Premium office spaces on both coasts with daily lunches provided
Professional Development
Access to premium coaching including leadership development
401(k) Plan
Competitive 401(k) plan offered
Dog-friendly office
Plenty of dogs to play with and make friends with in the SF office
Key Skills
- Apache Hive
- S3
- Hadoop
- Redshift
- Spark
- AWS
- Apache Pig
- NoSQL
- Big Data
- Data Warehouse
- Kafka
- Scala
