Top Remote Data & Analytics Jobs

Conduct experimental studies in natural language processing and machine learning, develop dark web monitoring tools, help transition research models to production, and publish findings in top conferences. Collaborate with teammates and propose innovative ML models to enhance products.

In this role, you will collaborate with stakeholders to leverage data for insights and systems improvement, stay updated on data science techniques, design effective experiments, and work on machine learning algorithms. You will also interact with data engineers to develop robust data pipelines and create tools that facilitate data access and visualization.

The Sr. Administrator for Design Data Manager will lead the transition from legacy PDM/PLM systems to a new DDM system, ensuring a seamless integration. Responsibilities include project management, data migration, stakeholder collaboration, training development, documentation maintenance, and process improvement.

The Product Analyst will analyze large-scale data to improve business performance, focusing on user engagement and conversion rates. Responsibilities include testing strategy implementation, defining KPIs, and creating visual dashboards. The analyst will collaborate with marketing and product teams to ensure data integrity and capture requirements.

The Organizational Transformation/Change Analyst will drive change initiatives using the ADKAR methodology, planning and executing awareness campaigns, and ensuring stakeholder alignment. Responsibilities include analysis, recommendations for engagement, and cultivating a change team.

The role involves implementing and supporting Credit and Debit Card programs, managing client training, documentation, and GoLive activities. The analyst will configure card functionality, support clients before and after implementation, diagnose issues, and create process documentation while ensuring data integrity during conversions.

The LLM Data Engineer will design, implement, and maintain data pipelines for Generative AI platforms, focusing on techniques like Supervised Fine Tuning and Reinforcement Learning from Human Feedback. Responsibilities include data source integration, optimizing workflows, managing various vector store technologies, and collaborating with teams to ensure data quality for AI/ML models.