Take the lead in building Monte Carlo's next-generation Machine Learning capabilities. This is a high-impact role where you’ll work on challenging and exciting projects that directly shape the future of data reliability, and collaborate with a tight-knit team of expert data scientists and engineers.

The VP of Data Engineering will manage the leadership team that supports Data Engineering, Data Science, and Data Analytics. They will act as lead architect and take responsibility for the ownership of the data platform itself, impacting revenue, strategic decisions, and products across the company.

As a Staff Data Engineer, you will be responsible for maintaining and operating the data platform that caters to machine learning workflows, analytics and powers some of the products offered to Apollo customers. You'll develop and maintain scalable data pipelines and build new integrations to support continuing increases in data volume and complexity. You will also implement automated monitoring, alerting, self-healing features while building the consumption pipelines.

Monitor real-time data streams from field sensors and responding to alerts, consistently following SOPs to investigate and localize real-time faults with minimal error, and working with Supervisors on ad-hoc data requests, following up during ongoing investigations.

This role is within the Data Science & Analytics team, focusing on building data tools, supporting experimentation, developing predictive models, and extracting data-driven insights. You will analyze complex data, leverage quantitative analysis, and collaborate with cross-functional teams to optimize marketing performance and drive business strategies. You need 3-5 years of data analysis experience.

You will work with the Associate Director of Strategy Analytics to evaluate and influence our global Freemium strategy. You'll play a crucial role in the growth and direction of Spotify as we grow to 600M+ users around the globe and monetize the product at scale. Above all, your work will impact the way the world experiences music, podcasts, and audiobooks!

Drive data-driven decision-making and process optimization by developing analytics models and enhancing reporting tools. The analyst will ensure seamless operations throughout the Amazon Prime activation process and collaborate cross-functionally with teams like Merchandising, FP&A, and Planning to align strategies and monitor performance.

Support cross-functional teams in optimizing automated workflow processing. You will oversee and maintain operational workflows to meet processing and service level targets, troubleshoot issues, coordinate resolutions with internal teams, and communicate status updates to external stakeholders.

As a Data Engineer at Sporty, you will play a critical role in ensuring the smooth processing and handling of data for our machine learning and data science initiatives. Your primary responsibilities will include designing, building, testing, optimising, and maintaining data pipelines and architectures for various aspects of our rapidly growing business.

The Carrillo Lab at The University of Chicago is seeking a highly motivated Data Science Analyst to work primarily with lab members on various projects to analyze large data sets. As a key member of our team, this position will develop analytical and statistical pipelines to quantify and identify meaningful insights from transcriptomic, proteomic, and imaging data.