Remote Data Jobs • Python

As a Senior Analytics Engineer, you will be crucial in optimizing our data infrastructure to empower teams across product development, engineering, data science, clinical operations, and finance. Your expertise will drive informed decision-making, contributing to our mission to accelerate the generation of actionable evidence to improve healthcare outcomes for everyone.

As a BI Analyst, you’ll be working with our fast-moving AI team that's building an intelligent assistant to transform how medical professionals work. The primary objective is to assist business in making decisions based on data, with a particular emphasis on producing global reports as the primary and most reliable source of information. You will be part of a Data Analytics team of 12 experts providing support to various departments.

Lead the development and implementation of intelligent automation solutions for our immigration processes. Responsible for designing, training, and deploying AI agents that support and streamline tasks such as visa tracking, document management, compliance monitoring, and client communications. Has strong expertise in artificial intelligence, machine learning, and natural language processing, with a focus on automating legal or regulatory workflows.

As a part of the Data Analytics function at Cribl, you will lead a team of data professionals dedicated to supporting our Revenue, Marketing, and Finance teams. You will oversee the business intelligence system, data analysis, and data strategy, playing a critical role in driving data-informed decision-making and fostering a culture of analytics excellence. Your ability to balance strategic vision with operational execution will be critical.

This role is part of Extend’s Revenue Analytics team, focused on developing strategic recommendations grounded in data to scale and drive revenue. The data scientist will identify growth and expansion opportunities that directly drive the company’s bottom line. If you’re excited about breaking down complexity and ambiguity into quantifiable impact, you’ll thrive on our team.

As a Solution Architect – Advanced Analytics, you will lead the design and delivery of cloud-native analytics architectures for enterprise clients. This role requires strong consultative and business communication skills. You’ll work with clients to assess needs, define solutions, and lead implementation across the data lifecycle. You’ll play a key role in articulating the business value and ROI of these solutions.

Nava is seeking a Data Engineer to modernize data architectures and pipelines in government programs. You'll design and implement data models and databases, improve data pipelines, enhance data security, and write code to process data more efficiently. You will deploy and operate mission-critical, highly-available, and scalable systems by adopting and defining standards and best practices in data engineering.

Looking to build a future where open source AI is the de facto standard? Spend some time at Mozilla.ai, working with our team of mission-driven ML and engineering experts on creating that future. We’re looking for practical, application-driven researchers to join our team for a fixed period of time. This role is best suited to a PhD student seeking an internship/project; a recent PhD graduate or an Applied Scientist working in tech companies interested in a short-term project.

Lead the development of data pipelines, transformations, data models, and analytic products in our data lake. You will represent the data team as a subject matter expert, and data model spokesperson. Develop strategic data and analytic products by bridging the gap between the business, data analytics, and data engineering.

This role involves developing high-quality applications by implementing testable and scalable code as an integral part of a development team. You will design, develop, and maintain robust data architectures, manage and build ELT and ETL pipelines between internal & external data stores, and leverage AWS services to build optimized solutions. Documenting data engineering processes, standards, and best practices is also required.