Top Entry Level Analytics Jobs

Develop and monitor fraud-detection models and pattern-recognition algorithms for lending products. Analyze large datasets using Python and SQL, identify emerging fraud trends, and collaborate with Fraud Operations to refine features and reduce false positives and negatives. Conduct ad hoc analyses, recommend risk and verification strategies, communicate findings to cross-functional partners, and support improvements to underwriting and verification processes.

Co-op supporting supply chain analytics initiatives through data engineering pipelines, business dashboards, predictive analytics, and forecasting models. The role involves working with large datasets, translating business needs into Power BI dashboards and analytical models, and helping deliver projects that improve operational decision-making. Candidates should understand machine learning, forecasting, cloud technologies, SQL, Python, relational databases, and supply chain operations.

Analyze and resolve pricing control exceptions involving fees, interest, refunds, and servicing activities. Review processes, build automated analytical workflows, develop reporting, and apply anomaly detection and responsible generative AI concepts. Partner with analysts, managers, product, operations, analytics, and technology teams to improve monitoring, documentation, and controls. Communicate findings clearly, manage multiple workstreams, and drive continuous improvement across card pricing operations.

Develops automation, data pipelines, databases, analytics, machine learning models, reporting tools, and web applications for package technology quality assurance. Analyzes manufacturing, product, and reliability data to support risk assessment and root-cause investigations. Collaborates with engineering teams, communicates findings, trains users, maintains software and reports, and shares analytics best practices across global teams.

Teaches undergraduate and graduate Business Analytics courses in a blended format. Responsibilities include developing syllabi and lesson plans, preparing and updating course materials, facilitating online and face-to-face learning, communicating expectations, creating and grading assessments, providing timely feedback, and integrating responsible AI practices into instruction. Faculty must complete ongoing training and professional development while supporting student learning in accordance with university requirements.

Leads content analytics by designing reporting systems, analyzing performance across digital platforms, generating data-driven insights, advising content teams, automating data collection and analysis, and presenting findings to senior and non-analytical audiences. The role also uses experimentation, data science techniques, LLM prompting, and agentic AI tools to improve content performance.

Own end-to-end analytics for a live-service game, including SQL analysis, A/B testing, metric reconciliation, dashboards, pipelines, simulations, forecasting, and applied ML. Translate findings into product, monetization, live-ops, and economy decisions. Use AI coding agents while validating their outputs, build reliable internal tools and services, maintain reporting, and communicate practical recommendations to technical and nontechnical stakeholders.

Leads executive-facing analytics for Home Lending Product Strategy, framing hypotheses, measuring impact, evaluating tradeoffs, and delivering recommendations and business cases. Coordinates analysts across matrixed teams, partners with Strategy, Product, Marketing, Finance, Originations, and Technology, conducts market and competitor research, and translates complex analysis into concise insights for senior decision-makers.

The posting identifies an Associate Director role focused on process data analytics at a cell and gene therapy company, but provides no specific responsibilities, qualifications, technologies, travel requirements, or clearance requirements.

Participate in a multi-week training then rotate across analytics teams (quantitative modeling, model risk, market risk, fraud, commercial analytics, client/employee experience, credit portfolio). Perform data analysis, develop predictive models, produce reports and visualizations, communicate insights to senior stakeholders, conduct market research, and support financial and regulatory reporting.

Tenure-track faculty member responsible for teaching undergraduate data analytics courses, developing curriculum, advising and mentoring students, conducting a focused research program, and contributing service to the program, university, and profession. The role emphasizes interdisciplinary instruction, inclusive pedagogy, experiential learning, and collaboration across academic disciplines.

Uses consumer and shopper analytics to support business strategy, uncover growth opportunities, and influence decisions. The role partners with Brand Management, Finance, Sales, R&D, and other functions, combining diverse data sources with human insights to deliver actionable recommendations. Responsibilities include communicating across teams, solving business problems, delivering real-time insights, and driving data-informed actions. Candidates need a relevant bachelor's degree, strong analytical and communication skills, creativity, initiative, and willingness to relocate.

Supports government-led analysis of integrated combat and weapons systems data. Responsibilities include analyzing training and test data, developing MATLAB or Python scripts for data extraction and transformation, preparing technical reports and presentations, communicating findings, documenting workflows, and collaborating with government and contractor teams. The role requires a DoD Secret clearance, U.S. citizenship, on-site work in Norco, California, and travel that may include U.S. Navy vessels.

Support client projects by structuring business problems, assessing data, selecting analytical approaches, conducting analyses, building and validating models, and translating findings into recommendations. The role involves quantitative consulting across industries, collaboration with clients and project teams, and potential work in AI, credit risk, sustainability, optimization, GenAI, and supply chain analytics. Business fluency in German and English and willingness to travel are required.

Supports client projects by structuring analytical problems, assessing data, selecting analytical methods, conducting analyses, building and validating models, and translating results into recommendations. Work may involve AI, predictive modeling, portfolio decarbonization, credit risk, optimization, chatbots, and supply-chain analytics. The role also includes client collaboration, communicating complex concepts clearly, and contributing to project teams across industries.

Build and own customer-facing analyses, dashboards, and reusable reporting for ECP Insights. Conduct customer discovery, define reporting needs, write SQL and Python or PySpark in Databricks, contribute dbt models, validate accuracy, explain methodologies, and help prioritize the product roadmap. Collaborate with product, engineering, and customer-facing teams while handling HIPAA-protected health information.

Own subscription marketing and lifecycle analytics for acquisition, conversion, retention, churn, CRM campaigns, engagement, attribution, cohorts, and spend efficiency. Write SQL, build dashboards, investigate data quality issues, evaluate offers and experiments, and translate findings into recommendations for marketing and cross-functional stakeholders.

Serves as the technical and client-facing link between Inca Digital’s data engine and high-stakes financial and government clients. Conducts OSINT, web scraping, enhanced due diligence, blockchain and crypto investigations; analyzes large datasets; audits and synthesizes technical findings into intelligence reports; briefs executive stakeholders; and coordinates cross-functional teams to align products with client needs.

Partners with Product leaders to solve ambiguous business problems through forecasting, modeling, segmentation, cohort analysis, scenario analysis, dashboards, and executive insights. Owns analytical initiatives from problem framing through implementation and measurable outcomes. Uses SQL across large enterprise datasets and applies generative AI and LLM tools to analyze structured and unstructured data, while validating AI-generated outputs. Prioritizes analytics requests, improves recurring workflows, and communicates recommendations to senior stakeholders.

As an Analyst, you will conduct analyses for Hive's offerings, support project delivery, collaborate with teams, and communicate project outcomes.

Teach undergraduate and graduate information systems and analytics courses, including course preparation, student assessment, grading, advising, and office hours. Participate in departmental, university, professional, and community service, contribute to student learning assessment, and maintain professional activity through scholarship, conferences, pedagogy, or industry practice.

Analyze multiple data sources, translate complex findings into actionable business insights, and communicate recommendations to cross-functional teams. The role supports Brand Management, Finance, Sales, and other partners by delivering real-time insights, influencing business decisions, solving ad hoc problems, and developing scalable analytics solutions that improve business results.

Uses consumer, shopper, market, and retail analytics alongside qualitative research to uncover insights, inform business strategy, evaluate advertising and promotional investments, and influence product, pricing, media, retail, and go-to-market decisions. Partners cross-functionally with Brand Management, Finance, Sales, R&D, and other teams to communicate findings, identify growth opportunities, and drive action.

Analyze mobile application data using Adobe Mobile Analytics, including iOS, Android, and hybrid app analytics. Utilize Sitecatalyst and Omniture for insights.

Monitor KPIs and business health across customers, segments, and systems; identify anomalies and investigate root causes across data, operations, and product changes. Build dashboards, alerts, and monitoring systems, collaborate with Engineering, Operations, and Product on issue triage, and create documentation and playbooks that improve response times and data quality practices.