Remote Data Jobs

We are looking for a DP-100–certified Azure Data Scientist passionate about applied Machine Learning and delivering measurable improvements for clients. As part of a growing innovation and technology team, you’ll contribute to the design, training, and deployment of AI and ML models within the Azure ecosystem, integrating ML models into real business processes that drive meaningful outcomes.

The Data Platform Engineering team is building the infrastructure to support a best-in-class decision engine. The role requires excellent communication to collaborate with Machine Learning Engineers, Data Scientists, and Analytics Engineers. The Data Platform Engineering team serves internal clients by maintaining infrastructure and tooling. The team advises backend and frontend teams to adopt the Event-Driven Data Mesh paradigm.

Act as a bridge between business areas and the technical team, ensuring that requirements are clearly identified, documented and aligned with project objectives. The ideal candidate will conduct detailed interviews with the client's business area, document the current state (AS-IS) of workflows, map data flows, detailing the interaction between entities, create documentation of functional requirements and use cases specific to automation and generate the solution design (To-Be) in collaboration with the RPA Specialist.

We are looking for a Machine Learning Engineer who is skilled and has significant experience in developing machine learning models. You will join a small, innovative team and lead efforts to advance our capabilities, drive model development, and support our vision for a future where Grass is transformative in the evolution of the internet.

Responsible for designing, developing, and maintaining large-scale data ingestion and transformation pipelines on Databricks. A key contributor in implementing modern DataOps practices, ensuring data reliability, scalability, and alignment with business requirements through the integration of data contracts and automated quality checks. Design, build, and optimize data ingestion and transformation pipelines using Databricks and other modern cloud-based data platforms.

Join the pricing and underwriting domain to bridge the gap between machine learning/data science and engineering. You will help build, publish, and maintain our complex data products and pipelines, key elements that have a significant impact on the company’s growth. Shape the architecture of data products designed for data analytics and data science.

We are looking for a passionate Senior Security Data Analyst/Python Developer to help us parse, transform, and analyze dirty data. The ideal candidate has a thorough understanding of Python, Data analysis techniques, AWS, ETL patterns, and Automation techniques. You will parse and transform structured and unstructured datasets, build Python-based automation for the parsing platform, and bring order to dirty and/or unstructured data.

In this high-impact role, you’ll take ownership of designing, building, and scaling the data pipelines and infrastructure that power our ML and AI models. You’ll work across ingestion, transformation, modeling, and orchestration — ensuring our data is reliable, accessible, and primed for analytics and machine-learning use cases.

Focusing on leading the design, development, optimization, and governance of enterprise-scale data platforms and pipelines on the Microsoft Azure cloud, this role requires a deep blend of technical expertise, architectural insight, and leadership skills. You will architect and implement scalable, secure, and cost-efficient cloud-native data solutions, primarily utilizing Azure Synapse Analytics.

This role is perfect for someone who thrives on autonomy, enjoys solving problems, and wants to make a real impact by turning data into actionable insights. You’ll be part of a collaborative, forward-thinking team where your curiosity and initiative will be valued. Tasks include monitoring data accuracy, creating dashboards and resolving data issues.