Develop and deploy machine learning (ML) models on large healthcare datasets, fostering a project through the entire model development lifecycle, including MLOps. Design rigorous experiments, optimizing model performance, interpretability, and actionable insights. Drive innovation by staying current with cutting-edge research in machine learning translating insights into scalable solutions. Collaborate with various teams to provide a data-driven perspective on business problems.
Develop production data science applications in Python, end to end. Design and develop new AI services from scratch. Maintain and enhance current data science pipelines in complex high-load applications. Collaborate closely with R&D and DevOps teams. Research, invent and adapt machine learning algorithms for dedicated business needs. Perform predictive and statistical modelling, and perform ad-hoc analyses as required.
As a Bioinformatics Research Engineer at SandboxAQ, you'll amplify our ability to make inferences about biology by utilizing multimodal data. Working closely with interdisciplinary teams, you will develop cutting-edge solutions at the intersection of machine learning, knowledge graphs, and genetic sequencing technology to vastly improve drug discovery and development on a social scale.
As a Data Scientist, you will be responsible for algorithm and methodology development for an innovative company using machine learning and remote sensing data. You will help quantify changes in soil organic carbon stocks in agricultural soils, deliver reliable results, and partner with our applied scientists and engineers to improve our models and processes that support a variety of carbon offset and Scope 3 projects.
Train and integrate Machine Learning and Deep Learning models and techniques including NLP, BERT, Transformers, Encoders, RAG, LLMs, and Agents. You will also develop machine learning pipelines, define and implement the metrics and evaluation of ML models, as well as apply statistical methods and hypothesis tests and perform data analysis and develop pipelines for processing big data.
As a Senior Manager Data Scientist, you will lead a team focused on developing advanced recommendation engines and deploying machine learning models into production environments, enhancing data-driven decision-making processes. This role involves mentoring a team, driving technical excellence, and fostering innovation in a dynamic, data-centric organization, leveraging expertise in Python and PySpark coding, along with experience in MLOps.
The SandboxAQ R&D team is looking for a PostDoc resident to help bring more AI to the domain of cybersecurity. A successful candidate will build models from scratch, fine tune existing ones, and run inference efficiently and design software systems around those models in close collaboration with our engineering department.
We are looking for an experienced applied data scientist to join our Data Science & Machine Learning Team focused on the application of data science, machine learning and AI approaches to understanding banking customer behavior and optimizing engagement marketing through our FinTech product platforms! You’re passionate about finding patterns, trends, and opportunities that can enable a better consumer banking experience, curious about what is driving KPIs and customer outcomes, and insightful in your analytical approach.
The AI Architect will drive customer outcomes, roadmap, and value realization for GenAI technology within accounts through hands-on delivery of ServiceNow’s GenAI capabilities and technical advisory activities. You will lead GenAI enablement programs and GenAI Impact accelerators for the broader Customer Excellence organization. Hands-on delivery of ServiceNow’s GenAI capabilities to customers and providing technical advice and guidance to best utilize ServiceNow’s GenAI technologies.
As a Senior Data Scientist, you will partner with project managers, strategists, and other members of the engineering team to aid clients in gaining deeper insights into their unique challenges and organization, effectively visualizing statistical findings. The role involves identifying data sets relevant to key research, communicating opportunities for product improvement, and collaborating with machine learning engineers.