Combine insurance domain expertise with full-stack data and analytics engineering.
Design rigorous data models, pipelines, and semantic layers for AI reliability.
Use SQL, Python, dbt, and Snowflake to build and maintain data infrastructure.
Nimble Gravity helps leading financial institutions and other clients adopt AI in meaningful ways. The company values teaching, facilitating, and influencing to help people embrace new ways of working.
Develop machine learning algorithms for device identification using noisy, unlabeled data.
Design supervised, semi-supervised, and unsupervised ML approaches.
Own projects from research through deployment to real-time services.
This partner company develops a high-volume, real-time identification platform for browsers and devices. It prioritizes engineering excellence and data-driven decisions, with a globally distributed team of specialists.
Lead the design and implementation of scalable data architectures for member communications, defining data models, contracts, and lineage.
Build and optimize production-grade data pipelines using Databricks, Apache Spark, PySpark, and SQL, ensuring reliability and performance.
Establish data-quality and governance practices, and partner with Privacy, Compliance, and Risk teams to manage sensitive member data securely.
Oportun is a mission-driven financial services company that provides responsible credit and savings to help members build a better financial future. Since inception, it has provided over $22.7 billion in credit and saved members more than $2.5 billion in interest and fees, reflecting a culture focused on impact and innovation.
Design and maintain data pipelines using SparkSQL and Pyspark within a central data lake.
Collaborate with cross-functional teams like Data Science, AI/ML, and other engineers to ensure high-quality data.
Champion Samsara’s cultural principles while building reliable, customer-facing data sets.
Samsara is the pioneer of the Connected Operations Cloud, enabling organizations to harness IoT data for safety, efficiency, and sustainability. As a publicly traded company, it fosters a culture of growth mindset and customer success, supporting a global team.
Analyze large, diverse datasets on business cash flow, credit, and repayment to identify product opportunities.
Partner with product and engineering to develop and commercialize data products and predictive models.
Lead Ocrolus’ analytics and data science efforts as a subject matter expert on SMB credit and mentoring.
Ocrolus is an AI platform for lenders, automating workflows with over 99% accuracy on nearly one million monthly credit applications. Trusted by 400+ customers, it is a remote-first team of builders and problem solvers.
Lead experimentation across product squads to shape hypotheses, design tests, and deliver clear readouts.
Design and maintain product metrics and dashboards to help teams track what matters.
Deliver deep-dive analyses on patient and clinician behavior to drive product decisions.
Ophelia is a healthcare startup making evidence-based treatment for opioid use disorder accessible through a telehealth platform. The company is a small, venture-backed team of physicians, scientists, and entrepreneurs operating in 16 states.
Build and lead the data analytics and outcomes research function, owning architecture through client-facing reporting.
Partner with engineering and product on implementation and delivery, and translate member and clinical data into actionable conviction.
Manage a small growing team and produce health economics evidence that demonstrates value to payer clients.
Nadia Care is a maternal health company reimagining pregnancy, birth, and postpartum care for underserved communities through doula support, care navigation, and virtual engagement. It is an early-stage, lean team that values empathy, collaboration, and resilience in a fast-paced environment.
Design, deploy, and optimize data and AI/ML systems on AWS end-to-end.
Maintain and evolve production platforms, monitoring for drift and improving reliability.
Partner with AWS Professional Services and client teams to align data and AI architecture with business goals.
We are an applied AI engineering firm building AI co-workers that integrate into enterprise operations and deliver measurable client results. Founded in 2009, we are a smaller, senior team with delivery centers in the US, Canada, Eastern Europe, and Latin America, averaging 15+ years of experience.
Manage ETL/ELT pipelines and data infrastructure on BigQuery to support reliable sales reporting.
Develop and maintain Looker Studio dashboards and optimize SQL queries for actionable insights.
Automate reporting workflows and investigate data anomalies to ensure data accuracy and integrity.
This company is building data infrastructure to power sales reporting, revenue operations, and business decision-making. It fosters a culture of autonomy, continuous improvement, and collaboration across sales and operational teams.
Design, develop, and maintain scalable data pipelines using Microsoft Azure Fabric and Databricks.
Build reliable ETL/ELT processes for structured and unstructured data and ensure production-ready integration solutions.
Collaborate with business stakeholders to translate data requirements into technical solutions and take end-to-end ownership.
This company is a technology organization seeking a Senior Data Engineer to build scalable data pipelines on Azure and Databricks. It offers a fully remote, collaborative environment with global stakeholders and a focus on engineering ownership.