Develop electrical system ontology for data centers which will be used to organize customer’s system data in a way where it can be used by AI & LLMs for customer facing products and services. Create and utilize tools to continuously monitor system telemetry from sensors, smart meters, and facility management systems to detect early signs of equipment degradation to help prevent service disruptions. Develop and deploy advanced anomaly detection models using machine learning and statistical methods to identify irregularities in power usage, voltage stability, cooling performance, UPS/battery behavior and more.
Join the Data Science team at Blackhawk Network to help drive business value through advanced data analysis and machine learning model insights. This role focuses on key features which include building and maintaining technology systems and performing data-driven analysis on key strategic issues. This role requires direct collaboration with Data Scientists, ML Engineers, Product, and Executive teams.
As a Data Scientist, you will develop machine learning algorithms, build data pipelines, and drive insights and predictive suggestions on products purchased. You will work with large amounts of data, handle data preprocessing tasks, and effectively communicate complex systems and algorithms to stakeholders.
In this role, you will develop interactive data visualizations that enable business insights and build a scalable analytical framework to monitor data quality across the organization. You will also work with data teams to deploy data quality across pipelines, set up processes to evaluate data issues, and create data quality standards, communicating insights to drive improvements and promote a data quality mindset.
This internship supports the Data Science team and offers hands-on experience in data science and statistical analysis within clinical or biomedical research settings. Interns will contribute to the development of machine learning models and assist in summarizing results and drafting manuscripts. You will have the opportunity to work closely with staff across departments and contribute to impactful research.
Looking for a passionate Data Scientist who enjoys solving real business problems with data and machine learning. You’ll take part in designing and delivering ML solutions end-to-end — from exploration and experimentation to deployment. If you like working with diverse data, collaborating with others, and seeing your models used in production, we’d love to meet you!
You will be responsible for the design and execution of product experiments and building robust machine learning pipelines to build the flagship personalization framework at Wealthsimple. Blend expertise in experimental design, predictive modelling and software engineering while effectively communicating with stakeholders.
In this position, you will drive the development of statistical models and machine learning algorithms to improve patient enrollment and trial management. You’ll work in a highly regulated healthcare data environment, ensuring compliance with privacy standards while innovating on predictive analytics. This role involves close collaboration with cross-functional teams to translate complex data insights into practical, impactful tools for the clinical research community.
Play a critical role in the foundation model development process, focusing on consolidating, gathering, and generating high-quality text data for pretraining, midtraining, SFT, and preference optimization. Create and maintain data cleaning, filtering, selection pipeline than can handle >100TB of data. Watch out for the release of public dataset on huggingface and other platforms.
This role involves automating data processing, generating actionable insights, and enhancing decision-making workflows by working with Large Language Models (LLMs) to design, develop, and integrate advanced AI solutions within our platform. The job will focus on building scalable, high-impact solutions that improve efficiency, accuracy, and user experience through natural language understanding.