Top Data & Analytics Jobs

Supports investment management data systems by improving data integrity, reporting, process automation, and operational efficiency. Processes and quality-controls portfolio data, troubleshoots systems, builds actionable reports, and assists with portfolio analysis, cash-flow projections, and financial modeling. Partners with investment, sales, client relations, and business teams while responding to data and reporting inquiries. The role also leverages AI tools to improve data access, workflow efficiency, and decision-making.

The Junior Data Analyst cleans, transforms, validates, queries, and maintains data for business intelligence. Responsibilities include database management, data quality assurance, statistical analysis, dashboard and report development, documentation, stakeholder collaboration, SOP support, and contributing to data lake or warehouse solutions. The role requires SQL, Excel, strong analytical skills, and the ability to support data-driven decisions in a fully on-site environment.

Leads advanced analytics for Sales Compensation, including quota processes, predictive modeling, reporting, data integration, ETL, and business intelligence. Analyzes data across applications, resolves discrepancies, defines data mappings, develops scalable automation and reporting solutions, collaborates with business stakeholders and DBAs, and delivers recommendations affecting multiple business organizations.

Leads multidisciplinary data and analytics teams, setting strategy, standards, priorities, and staffing. Oversees data pipelines, analytical databases, predictive models, reporting workflows, and business intelligence initiatives. Partners with business stakeholders to translate needs into technical solutions, communicate insights, improve processes, and drive business value. Manages recruitment, coaching, performance, retention, and development while advancing analytics adoption and data-driven decision-making across the organization.

The Data Analyst will organize, validate, transform, and reconcile data from multiple healthcare practice management systems. Responsibilities include writing SQL and Python scripts, supporting a centralized data warehouse, building BI dashboards, validating data quality, analyzing business trends, documenting data processes, and partnering with Finance, Operations, Marketing, and leadership to deliver actionable insights.

Analyzes digital, marketing, e-commerce, customer, and commercial data to identify growth opportunities and improve customer engagement. Responsibilities include evaluating campaigns and funnels, measuring attribution and ROI, building Power BI dashboards, integrating CRM and marketing data, supporting A/B testing, conducting statistical and predictive analyses, and presenting actionable recommendations to stakeholders.

Designs, develops, tests, and deploys reports, dashboards, and analytics solutions using UKG Pro HCM or Pro WFM. Provides report design, application build support, training, testing, go-live support, change management, documentation, and client consultation during implementations and migrations. The consultant also contributes to internal methodologies, mentors colleagues, and supports sales and marketing initiatives. The role requires SQL, BI tools, advanced Excel, UKG reporting expertise, and up to 10% nationwide travel.

Own measurement strategies for large omnichannel brands, including test design, marketing mix modeling, incrementality analysis, attribution interpretation, and budget recommendations. Translate complex findings into actionable guidance for executives and marketing teams, support prospect conversations, identify customer and product gaps, and collaborate with Product, Data Science, and Customer Success. The role requires strong paid media expertise, omnichannel fluency, statistical measurement literacy, and the ability to communicate uncertainty and recommendations clearly.

Supports payment fraud prevention through system monitoring, fraud trend research, false-positive analysis, quality checks, and strategy evaluation. Helps develop risk-based fraud controls and improve customer experience. Identifies automation opportunities and assists with Power Automate, VBA, and basic scripting projects to reduce manual work, streamline operations, and improve data usage and team efficiency.

Leads and develops product, marketing, and data analysts while overseeing analytics strategy, prioritization, technical standards, experimentation, reporting, and data quality. Partners with Product, Marketing, Finance, Engineering, and recruiting to deliver trusted insights, scalable self-service analytics, and team growth. Requires strong SQL and Python skills, modern data-tool experience, analytics leadership, stakeholder communication, and at least five years in data roles with two years managing teams.