Top Data & Analytics Jobs

Lead data engineering and machine learning initiatives by designing, architecting, developing, and supporting GCP data pipelines. Create information architecture documentation, estimate and plan technical work, collaborate with project teams and business analysts, and translate requirements into technical designs. Develop Python-based ELT pipelines, optimize BigQuery SQL, support CI/CD, and provide technical leadership to projects and teams.

Build data extraction, transformation, loading, modelling, analytics, machine learning, and dashboard solutions for teaching and learning data. Partner with faculty to gather requirements, generate insights, analyze student learning behavior, and develop Power BI visualizations. Train and advise lecturers on dashboard use and provide knowledge transfer on analytics and modelling.

Analyze large-scale transactional, operational, and customer datasets; build visualizations, machine learning models, and experiments; translate complex findings into clear recommendations for operational teams and executives; and apply analytical software, databases, visualization tools, and programming languages in a fast-paced blockchain environment.

Leads enterprise master data governance across customer, product, supplier, and transaction domains. Establishes data standards, architecture, quality metrics, systems of record, and warehouse structures. Partners with IT, analytics, and business leaders to enable reliable reporting, AI, customer segmentation, pricing, sourcing, and operational insights. Drives data cleanup, enrichment, continuous improvement, cross-functional governance, training, and data literacy while maintaining business ownership and accountability for enterprise information integrity.

Leads enterprise master data governance across customer, product, supplier, and transaction domains. Establishes data standards, architecture, quality metrics, systems of record, and governance processes; partners with IT, analytics, and business leaders to enable reliable reporting, AI, customer segmentation, sales growth, sourcing, pricing, and operational decisions. Oversees data enrichment, architecture approvals, corrective actions, change management, data literacy, and cross-functional implementation of enterprise information standards.

Entry-level role supporting data, analytics, technology and transformation projects. Participate in classroom training, complete assigned projects, follow coding and documentation best practices, build data-driven presentations, and analyze data to support decision-making while collaborating across Data-Analytics, Technology, and Transformation teams.

Build and maintain scalable web crawlers to extract, validate, and structure product data from eCommerce sites. Use AI-driven techniques, browser automation, proxies, and APIs to handle dynamic content and anti-bot measures. Monitor performance, clean large datasets, collaborate with Product/Engineering/Data teams, and continuously improve crawling frameworks and automation.

Lead design and implementation of scalable data models and analytical tooling for Consumer Product. Partner cross-functionally to translate business needs into reliable SQL/Python data products, dashboards, and automated pipelines using engineering best practices (CI/CD, testing, version control, monitoring). Drive data-informed strategy and manage long-term infrastructure while supporting ad hoc requests.

As a Senior Machine Learning Engineer, you'll build and deploy ML models for risk and fraud detection, leading technical efforts and collaborating cross-functionally.

The Officer, Model Risk Management validates bank-wide models, ensuring compliance with regulations. Responsibilities include developing testing plans, assessing model performance, reviewing documentation, and collaborating with stakeholders for effective model governance.

The Strategy & Analytics Senior Lead will drive product decisions through analysis, partnering with cross-functional teams to generate insights and enhance operational processes.

Lead and execute analytics across client engagements: measurement strategy, reporting, advanced measurement (attribution, incrementality, experimentation), AI-enabled analytics, and team leadership. Ensure analytics inform media planning, deliver scalable measurement frameworks, and drive client-facing insights tied to business outcomes while mentoring an analytics team.

Lead analytics planning and delivery across client engagements, translate data into business outcomes, drive advanced measurement (attribution, incrementality, experimentation), integrate AI and automation into workflows, mentor and grow analytics teams, and partner cross-functionally to inform media strategy and optimize performance.

Conduct rigorous research using statistics and machine learning to extract patterns from datasets. Implement algorithms, back-test models, and document findings.

Lead hands-on analytics initiatives for Global Supply Chain using BI, ML/AI, and process improvements. Collaborate with stakeholders and IT to design, implement, and scale reporting, dashboards, POCs, and SOPs. Manage projects, train staff, and improve manufacturing data quality to drive operational performance.

Front-office commodities quantitative analyst supporting portfolio managers and traders. Develop and maintain statistical, econometric and ML models, risk and pre-trade analytics, systematic and option strategy research, and scalable Python tools across energy, power, metals, agriculture and soft commodities.

Leads Pacsun’s enterprise business intelligence, data warehouse, analytics, and system integration strategy. Oversees BI developers and analysts, MuleSoft integrations, retail systems including Microsoft D365 and Manhattan OMS/POS, ETL and OLAP initiatives, data architecture, modeling, validation, and AI-driven predictive analytics. Partners with business and IT leaders on ERP and financial system transformation, resolves technical challenges, documents data designs, and mentors the BI team.

Audit and improve human and model-generated data outputs for accuracy, consistency, and policy compliance. Provide actionable feedback, clarify evolving guidelines, support annotators, coach new team members, monitor workflows and blockers, identify recurring issues and edge cases, participate in calibration discussions, and document findings to improve team performance and quality at scale.

Leads General Liability insurance pricing analytics, predictive modeling, model governance, and data science strategy. Develops, validates, deploys, and monitors advanced statistical and actuarial models supporting underwriting, profitability, and pricing decisions. Partners with actuarial, underwriting, product, claims, finance, and technology teams; communicates recommendations to senior leaders; manages complex projects; and leads, coaches, and develops analytical staff.

The Business Analytics Manager develops operational reports, dashboards, scorecards, and business intelligence solutions for Contact Center Operations. Responsibilities include analyzing customer and operational data, identifying trends and root causes, automating reporting processes, modernizing analytics platforms, applying AI-enabled tools, and presenting actionable recommendations. The role partners with business, technology, product, and analytics stakeholders to improve performance, customer experience, reporting reliability, and data-driven decision-making.

Leads the strategy, architecture, and execution of an enterprise data platform supporting analytics, machine learning, operational systems, and AI applications. Manages and mentors data platform engineers while remaining hands-on with architecture, reliability, technical direction, and troubleshooting. Oversees pipelines, orchestration, governance, security, observability, data contracts, migrations, and platform operations. Partners cross-functionally to translate business needs into scalable technical solutions and communicates decisions to technical and non-technical stakeholders.

Manage analytics consulting projects for Life Sciences clients, delivering marketing, commercial, Real World Data, market mix modeling, and predictive modeling solutions. Responsibilities include developing analysis plans, analyzing healthcare datasets, leading client discussions, presenting recommendations, ensuring quality and timely delivery, and managing team engagement. The role requires strong client-facing consulting skills, knowledge of biopharma commercial analytics, patient analytics, payer and market access concepts, and clear written and verbal communication.

Design and build end-to-end data pipelines and integrations on Databricks, implement medallion architectures, develop streaming and NiFi pipelines, integrate purpose-built stores, operationalize ML/MLOps (training, deployment, monitoring), and explore LLM/RAG generative AI solutions while enforcing data governance, security, and performance for large-scale analytics.

Collect, analyze, and interpret complex datasets to create and maintain customer-facing Tableau reports; collaborate with customer services and development teams to scope reports and data models; investigate data accuracy issues and communicate insights to stakeholders.

Contract role combining actuarial science, risk management, and AI to improve portfolio performance. Responsibilities include loss and combined ratio analysis, portfolio risk assessment, catastrophe and exposure modeling, stress testing, and integrating ML to enhance pricing, reserving, and risk selection while collaborating with underwriting, finance, and product teams.