Remote Data Jobs · Python

Conduct comprehensive failure analysis on AI agent performance across finance-sector tasks to identify patterns, root causes, and systemic issues in our evaluation framework by analyzing task performance across multiple dimensions (task types, file types, criteria, etc.). Key responsibilities include statistical failure analysis, root cause analysis, dimension analysis, reporting & visualization, quality framework, and stakeholder communication.

Lead the design, development, and operation of a modern enterprise data platform, driving cloud-based initiatives and enabling actionable insights across the organization. Manage a team of architects, engineers, and specialists, fostering a culture of innovation, technical excellence, and collaboration. Balance strategic oversight with hands-on involvement in data architecture, platform enablement, and integration across diverse tools and technologies.

In this strategic role, you will lead high-impact initiatives at the intersection of data, analytics, and artificial intelligence. You will work across global teams to modernize data capabilities, drive AI adoption, and accelerate digital transformation across multiple business functions. Acting as a bridge between business needs, analytics potential, and emerging technologies, you will shape use cases that deliver measurable business value.

In this senior leadership role, you will define and execute the data and analytics strategy for a global digital organization, transforming diverse data sources into actionable intelligence that drives growth. You will lead and expand a high-performing team, oversee the full analytics and BI ecosystem, and shape how insights guide decisions across content, marketing, product, and revenue operations.

As a Senior Data Scientist, you’ll report to the Data Science Manager and work closely with both the Data Science and Engineering teams. You will play a crucial role in developing models for complex parts of our business, analyze large datasets, identify patterns, and develop a variety of model types. You’ll also contribute to the improvement and re-design of current models, collaborating with cross-functional teams to translate insights into actionable solutions.

We are looking for a Senior Data Engineer with deep expertise in Azure and SQL to build, optimize, and deliver scalable data solutions across multiple client projects. In this role, you will work independently as well as part of a broader data team, engaging directly with customers, translating business needs into technical solutions, and ensuring best practices across data architecture, governance, and performance.

The Commercial Business Analyst at Big Health develops a deep understanding of program, clinical, and commercial performance to answer key questions about the health and impact of our digital therapeutics. This role translates complex healthcare and commercial data into clear stories, insights, and recommendations that drive revenue growth, customer retention, and measurable clinical and economic value.

Play a key role in transforming complex datasets into actionable insights that drive business decisions and support growth initiatives. Work closely with internal teams, including managers and executives, to analyze historical and operational data, design dashboards, and create reports that inform strategic initiatives. This role requires proficiency in data querying, visualization, and workflow optimization.

Maintain, troubleshoot, and optimize a data ingestion pipeline built with Java and Python. Implement new features and improvements that keep our systems efficient and scalable. Write clean, testable, and well-documented code. Participate in code reviews and share ideas that raise the bar for our engineering practices. Stay curious and up to date with emerging technologies and best practices in data engineering.

You are a seasoned Data Engineer with a passion for designing and implementing enterprise-scale data warehouses and pipelines that power data-driven decisions. You thrive on solving complex problems related to data modeling, governance, and performance, ensuring data is accessible and reliable for millions of users and internal stakeholders. You excel at translating business needs into robust, secure, and scalable data solutions.