Remote Data Jobs • AWS

Work on a cloud-native analytical database system built for multimodal (often time-series) data. The system is built in Rust and makes extensive use of Apache Arrow and supports specialised queries to handle robotics-style multimodal logs. Design, implement and operate the core pieces that make sure this data-intensive system is highly scalable, reliable and observable.

Work at the intersection of data science and software engineering, collaborating directly with customers and their data. Derive meaningful insights from large amounts of data, comfortable running data assessments or building ML-based scoring models. Customer obsessions is your north star as you dive deep into problems and propose novel solutions, also identify and participate in important company-building initiatives.

As a Data Analyst, AWS Analytics on the Exam Config team, you will play a critical part in supporting data management and conducting root cause analysis to ensure the reliability and accuracy of Exam Config systems. Leveraging your AWS expertise, advanced SQL skills, and strong problem-solving abilities, you will work with complex data sets, automate key processes, and drive efficiency. You are independent and proactive with exceptional problem-solving skills.

Help companies from around the world prevent and recover from cyber attacks by providing critical insights from our data. Play a major part in raising the bar as we continue our growth. Architect and build data pipelines in the cloud that are robust, scalable, and performant for products used by a growing global customer base.

The intern will contribute to building scalable data solutions that support CALSTART's mission while gaining hands-on experience in cloud-based data engineering and data science. This project will focus on creating a data lake environment, developing automated data pipelines, and designing powerful visualizations to gain insights into clean vehicle adoption, infrastructure planning, and sustainability efforts.

Reporting to the Senior Manager of Development and Operations, you will be an expert in designing and developing end-to-end data solutions from source data ingestion, ETL process, visualization, and to business insights delivery. You will identify automation opportunities in existing data pipelines and propose design of the automation process. You will collaborate with Engineering teams to discover and use data being introduced into the environment.

You will engage with stakeholders to translate business problems into technical solutions, design and test personalization solutions, create forecasting models using time series and machine learning, and solve complex optimization problems. You will stay updated on the latest research in personalization techniques and work closely with product managers, MLOps engineers, and software developers to deploy end-to-end solutions.

Support the team’s efforts in building both statistical and predictive models that help us identify trends and better operate our business. Design, develop, and deploy predictive models to enhance decision-making and improve healthcare outcomes. Conduct in-depth statistical analyses to derive actionable insights from complex datasets.

Looking to build the next generation of data pipelines and applications across the development of innovative new systems and solutions using a rapidly changing landscape of emerging technologies, including generative AI and large language models. Primary focus will be building reliable, scalable, and efficient pipelines for use in LLMs and crafting our vision for LLM analytics. Responsible for designing, building, and scaling data pipelines across a variety of source systems.

As ML Lead, you’ll drive the strategy, architecture, and execution of our ML initiatives - from recommendation systems to predictive analytics. You’ll have a chance to lead a small ML team (starting with hands-on work), define best practices, and build systems that directly impact the product and business outcomes.