Top Hybrid Data Analysis Jobs

As a Senior Data Scientist in Product Analytics, you will analyze data to guide product decisions, support product managers, and improve financial stability for users.

Provide accurate valuations and risk assessments for single-family homes using internal tools and pricing model outputs. Incorporate local market knowledge, collaborate with sales, homes, data science and engineering to improve pricing operations and ensure competitive, consistent offers.

The Geospatial SAR Imagery Analyst Scientist analyzes SAR data to improve machine learning algorithms, curating imagery for data sets and recommending strategies for data gaps.

Analyze warranty and reliability data to identify trends, risks, and cost drivers; develop dashboards and reports; support root-cause analysis, cost forecasting, and customer negotiations; ensure data integrity and drive continuous improvement across cross-functional teams.

Support data and customer-success functions by entering, cleaning, and analyzing data; maintain databases; assist clients with LevPro configuration, demos, onboarding, and implementation; identify process improvements and help build client relationships.

The Senior Data Analyst gathers BI requirements, analyzes enterprise and offline datasets, writes and optimizes SQL queries, and builds dashboards using Power BI, Tableau, and Domo. The role translates business needs into technical specifications, designs dashboard wireframes, validates data, documents processes, and collaborates with engineering, product, and business teams. Knowledge of the US trust business is essential for interpreting data within financial and regulatory contexts.

Own pricing programs and advanced SQL analyses across competitive matching, price perception, margin optimization, experimentation, and pricing operations. Design and evaluate pricing tests, partner with engineering and data science on automation, and translate analytical insights into scalable business processes and recommendations. Collaborate cross-functionally with merchandising, supply chain, marketing, and private brand teams to improve customer trust, pricing consistency, and business performance.

Build and launch benchmark, thematic, factor, strategic beta, and multi-asset indexes from concept through market launch. Conduct quantitative research, data analysis, signal testing, back-testing, portfolio construction, risk modeling, and statistical testing. Use Python and AI tools to automate workflows and accelerate methodology development. Create prototypes, dashboards, research materials, methodology documents, and client-facing narratives while partnering with research, product, technology, operations, and commercial teams.

Supports enterprise data initiatives through data quality checks, cleanup, documentation, dashboards, reporting, and prototype development. Learns data governance, security, cloud platforms, SAP, analytics tools, and system integration. Collaborates with senior IT leaders and cross-functional teams while developing foundational skills in Python, SQL, data preparation, cloud technologies, predictive analytics, and enterprise applications.

Analyze sales, marketing, and customer success performance, including pipeline, funnel conversion, campaigns, retention, and revenue drivers. Build and maintain dbt models and marts using Salesforce and modern data-stack tools, while owning data quality and documentation. Contribute to Lighthouse, a BI-as-code platform, and develop AI-assisted analytics workflows. Partner with stakeholders to frame ambiguous questions, deliver recommendations, and communicate progress in two-week sprints.