Top Senior Level Data & Analytics Jobs in Boise, ID

The VP, Enterprise Data Sales at Predactiv will lead the adoption of DaaS solutions within the Advertising & Marketing ecosystem. Responsibilities include developing sales strategies for complex enterprise prospects, enhancing customer engagement with the Predactiv Data Platform, preparing technical presentations, and identifying upsell opportunities to drive revenue growth.

As a Senior Machine Learning Engineer at Concurrency, you'll design and engineer ML systems, collaborating with data science teams to solve diverse customer problems. You'll leverage your expertise in supervised, unsupervised, and deep learning, using tools like Python and SQL, while influencing project direction and designing production solutions in a cloud development environment.

As a Senior Data Analyst at Privacy.com, you will own analytics for the consumer business, produce insights for stakeholders, develop data models, partner with customer experience teams, and design A/B tests to enhance user experience.

As a Senior Analytics Engineer at Amplify, you'll create analytical models to support educational products and provide insights to school administrators and internal business partners. You'll collaborate with data scientists and engineers to ensure data accuracy and security while building cohesive data marts from various systems. Additionally, you will participate in agile processes, mentoring, and continuous learning within a multi-functional team.

The Sr. Analyst Relations Manager will enhance Databricks' visibility in the market by developing an analyst relations program. Responsibilities include building relationships with key industry analysts, managing analyst requests, and staying updated on industry trends to inform product strategies. The role collaborates with internal teams to coordinate analyst engagement and support marketing activities.

The Data Scientist at LeaseLock develops machine learning models and provides analytical insights to support risk controls, financial forecasting, and sales strategies. Key responsibilities include predicting property risk, delivering data-driven strategies, and identifying data inconsistencies to enhance modeling frameworks.

The Data Scientist will develop and automate key metrics to support business objectives, source and clean data, perform data analysis using statistical and machine learning techniques, create visualizations, and collaborate with teams to provide analytical support. They need to document processes and stay updated on data science trends.