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FiltersLaunchDarkly is seeking an experienced Data Analytics Engineer to build high-quality data models and data products that directly influence sales strategy and revenue reporting. You’ll join our Data Analytics and Engineering team in the Technology organization and work closely with embedded revenue analysts, salesforce, software engineers, and the revenue operations team.
The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch, someone who can assist with optimizing the different aspects of the modeling process and improving a variety of Swish products. They will engineer custom solutions to solve complex data-related sports challenges across multiple leagues. This position is 100% remote.
Define the roadmap, architecture, and systems that transform how data drives growth across the business. This role will blend strategy, architecture, and execution to turn Rockbot’s data into a growth engine, building and leading a centralized data organization spanning analytics, business intelligence, and data-driven business processes. As the most senior data leader, you will partner with various teams to define and operationalize the data roadmap.
Build out our foundational processes for generating and surfacing model performance metrics, including crafting + calculating the metrics and building python rails. Act as point of contact for Strategic Financial Partners and manage their model governance needs. Regularly conduct performance and exploratory analyses to establish the quality of model outcomes.
As a Staff Machine Learning Scientist, you will be a key technical leader responsible for designing and building our core deep learning models. You will tackle some of our most challenging technical projects, translating high-level scientific goals into robust and effective neural network architectures that can interpret complex mass spectrometry data.
Administer, monitor, and ensure the continuous operation of the Data Warehouse (DWH) infrastructure, perform regular tuning of SQL queries, indexes, partitioning, and DWH configuration parameters to achieve maximum processing speed. Configure and control user access rights in compliance with internal security policies. Develop, implement, and test backup strategies and Disaster Recovery Plans. Implement and maintain monitoring systems, analyze logs, and provide warnings for potential issues.
We are looking for a Data Analytics Engineer to build, optimize, and maintain the analytical data layer that powers decision-making across the organization. You will transform business requirements into reliable, well-modeled datasets using dbt, SQL, and cloud data warehouses. This role combines data modeling, documentation, data quality design, and close collaboration with analysts, engineers, and product teams to ensure consistent, trustworthy reporting.
As a Senior Data Scientist on Lime’s Rider DSA team, you will play a critical role in helping us understand our riders and uncover the drivers of retention. You’ll focus on experimentation, product analytics, and data deep-dives that surface actionable insights for product and business teams. Partnering with Product, Engineering, and Operations, you’ll help shape strategy on initiatives like early-funnel adoption, second-month retention, and loyalty programs.
You will work with Engineers, Data Scientists, Managers, and others to understand their needs, and actively work to build datasets to tackle these challenges. Collaboratively refine and evangelize a comprehensive framework for integrating data-thinking into the software development lifecycle for product teams. Design, architect, and maintain core marketing datasets, data marts, and feature stores that support a blend of mature products and features. Drive data quality and best practices across different business areas.
We are looking for a highly skilled Senior Data Engineer with strong experience in designing, building, and maintaining scalable data solutions. The ideal candidate has a deep understanding of ETL processes, big data technologies, and modern analytics platforms, and is comfortable working in fast-paced, data-driven environments. Key Responsibilities include designing, developing, and optimizing robust ETL pipelines to support data ingestion, transformation, and processing at scale.