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A day in the life: At Hertz, our senior data scientists are responsible developing and defining best practices for analytical methods to generate informative research, reports, visualizations, and dashboards using internal and external data to provide actionable and strategic insights. This includes fostering collaboration, building partnerships, co-developing products, sharing knowledge, providing insights and valuable predictive information to business teams and leaders to highlight potential risks and opportunities that initiate the drive for change.

Hertz is the largest worldwide airport general use car rental brand, operating from approximately 10,090 corporate and licensee locations in approximately 145 countries. Our Dollar and Thrifty brands have approximately 1,400 corporate and franchise locations in approximately 75 countries. Hertz is the number one airport car rental brand in the U.S. and at 130 major airports in Europe. Hertz is an inaugural member of Travel + Leisure's World's Best Awards Hall of Fame and was recently named, for the thirteenth time, by the magazine's readers as the Best Car Rental Agency. Hertz was also voted the Best Overall Car Rental Company in Zagat's 2013/14 U.S. Car Rental Survey, earning top honors in 14 additional categories, and the Company swept the global awards for Best Rewards Program and Best Overall Benefits from FlyerTalk.com. Product and service initiatives such as Hertz Gold Plus Rewards, NeverLost®, and unique cars and SUVs offered through the Company's Adrenaline, Prestige, Green Traveler, and Dream Car Collections, also set Hertz apart from the competition. Additionally, Hertz owns the vehicle leasing and fleet management leader Donlen Corporation and operates the Hertz 24/7TM hourly car rental business. The Company also owns a leading North American equipment rental business, Hertz Equipment Rental Corporation, which includes Hertz Entertainment Services. More information about the Company can
		be found at <a href="http://www.abouthertz.com/" target="_blank">www.abouthertz.com.</a> 
		 
	Learn more about Hertz by visiting <a href="http://www.hertz.com" target="_blank">www.hertz.com</a>
 										Hertz is an Equal Opportunity Employer.

The Hertz Corporation

Sr Data Scientist

ea_via_bold

OTHER

Deliver AI-driven solutions that measurably improve key product or operational metrics (e.g., revenue uplift, cost reduction, consumer satisfaction, platform efficiency, prediction accuracy, latency reduction). Develop, fine-tune, and optimize machine learning and generative AI models including prompt engineering strategies and structured evaluation frameworks for LLM-based systems to ensure performance, scalability, and reliability.

Repay - Realtime Electronic Payments

Data Scientist

Broadbean

Data Visualization: Createcompelling data visualizations tocommunicate findings effectively to bothtechnical and non-technical stakeholdersusing tools like Tableau, Power BI, orPython libraries. A Data Scientist with 5 to 10 years of experience is a critical asset to an organization, capable of transformingdata into actionable insights, buildingpredictive models, and driving data-drivendecision-making.

4P Consulting

While we advocate for using the right tech for the right task, we often leverage the following technologies: Python, PySpark, the PyData stack, SQL, Databricks, our own open-source data pipelining framework called Kedro, Dask/RAPIDS, container technologies such as Docker and Kubernetes, cloud solutions such as AWS, GCP, and Azure, and more. 5+ years of deep technical experience in machine learning, knowledge graphs, agents, evaluation frameworks for agentic outputs, graph neural networks, deep learning, computer vision, and statistics-related work.

McKinsey & Co Inc

Senior Data Scientist - Life Sciences.AI

A Data Scientist with 5 to 10 years of experience is responsible for leveraging data to uncover insights, create predictive models, and drive data-driven decision-making within an organization. This role requires advanced analytics, machine learning expertise, and strong problem-solving skills to extract actionable intelligence from large and complex datasets.

Data Scientist 2 4P/187

This professional combines technical expertise, advanced analytics, and strategic thinking to transform data into actionable insights, optimize decision-making, and mentor emerging talent, ensuring sustainable growth in data-driven operations. Overview: A Data Scientist with 5 to 10 years of experience plays a pivotal role in leveraging data to uncover actionable insights, create predictive models, and drive informed decision-making within an organization.

Data Scientist 2 - 4P/114

This role focuses on developing, optimizing, and enhancing intelligent solutions using Generative AI technologies, including Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Model Context Protocol (MCP) servers. Norfolk Southern also has the most extensive intermodal network in the eastern U.S., serving a majority of the country's population and manufacturing base, with connections to every major container port on the Atlantic coast as well as the Gulf of Mexico and Great Lakes.

Norfolk Southern Corp

Lead Data Scientist - GenAI

The Principal Scientist should have experience across the important technologies in the sensor technology space, including signal processing, RF systems hardware, antenna technology, electromagnetics, system integration, field testing, data collection, missions and CONOPs, along with a proven track record of delivering quality results to customers in the Department of Defense (DoD) and Intelligence Communities (IC). STR is seeking a Principal Scientist to work across the company to develop a cohesive strategy and provide direction, technical oversight and review across the portfolio of sensing and counter-sensing programs, particularly in the development of new RF technologies, electromagnetic analysis/modeling and antenna development.

YEAR

Principal Scientist

This role sits at the intersection of Workday's Data Cloud business, partnering directly with the Data Cloud organization (SVP/GM, Product Management, Engineering, and GTM teams) to bring analytical rigor and powerful business insights to a fast-growing, consumption-based product line. We know that flexibility can take shape in many ways, so rather than a number of required days in-office each week, we simply spend at least half (50%) of our time each quarter in the office or in the field with our customers, prospects, and partners (depending on role).

Workday Inc

Sr Product Data Scientist

THOR Data Engineering develops and maintains five key financial transaction Enterprise Information Products (EIPs)—THOR (Transaction History Opportunities Recognition), Non-Financial Activity (NFACT), THOR Global Wealth and Investment Management (GWIM), Private Bank (THORPB), and Sentinel THOR (STHOR)—within the THOR Authorized Data Source (ADS). By providing AI and model risk governance, AI-driven solutions, and critical transaction data assets, DSTRO delivers the controls, infrastructure, and insights needed to strengthen risk management, enhance operational effectiveness, and drive enterprise value.​.

Bank of America

Data Scientist I

Collaborate with engineering and analytics partners to move models into reliable production workflows, then investigate performance changes and recalibrate, retrain, or replace models when needed. • Master's degree or higher in statistics, mathematics, computer science, engineering, operations research, economics, or another quantitative discipline — or equivalent hands-on experience shipping production models.

FairSquare

Lead Data Scientist - Growth & Marketing Models

BreezyHR

You should be able to start with billions of financial transactions, use HPCC/ECL to transform those transactions into meaningful behavioral and relationship features, identify patterns associated with fraud or financial crime, validate those patterns historically, and work with engineering to turn them into scalable production detection capabilities. Python, R, and traditional machine-learning frameworks may be used where appropriate, but the successful candidate must be comfortable performing substantial analytical work against large-scale financial datasets using the DataSeers HPCC/ECL environment.

DATASEERS INC

Data Scientist, Financial Crime & Fraud Analytics

HiringThing

This position involves analyzing large-scale IoT data from water meters, building predictive models, and collaborating with cross-functional teams to deploy data science solutions into production. As a Data Scientist, you will be responsible for developing and implementing machine learning models and analytical solutions that support our water utility intelligence platform.

Neptune Technology Group

You will design, architect, and deliver some of WBD’s most complex and business-critical AI systems, directly influencing how the company creates, distributes, personalizes, monetizes, and optimizes content across streaming, linear TV, advertising, and direct-to-consumer platforms. Design and build enterprise-grade Agentic AI systems, including autonomous and multi-agent workflows that leverage reasoning, tool use, planning, memory, and orchestration to execute complex business processes.

Warner Bros. Discovery

Sr. Principal Data Scientist (Agentic AI)

It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market leading capabilities in AI, generative AI, cloud and data, combined with its deep industry expertise and partner ecosystem. Important Notice: Compensation (including bonuses, commissions, or other forms of incentive pay) is not considered earned, vested, or payable until it becomes due under the terms of applicable plans or agreements and is subject to Capgemini's discretion, consistent with applicable laws.

About Capgemini

A global leader in consulting, technology services and digital transformation, Capgemini is at the forefront of innovation to address the entire breadth of clients’ opportunities in the evolving world of cloud, digital and platforms. Building on its strong 50-year heritage and deep industry-specific expertise, Capgemini enables organizations to realize their business ambitions through an array of services from strategy to operations. Capgemini is driven by the conviction that the business value of technology comes from and through people. It is a multicultural company of over 200,000 team members in more than 40 countries. The Group reported 2018 global revenues of EUR 13.2 billion (about $15.6 billion USD at 2018 average rate).

Visit us at www.capgemini.com. People matter, results count.

Capgemini SE

Capgemini Invent - Data Scientist

The ideal candidate applies a blend of mathematical, statistical, computational, and domain-specific expertise to analyze data, develop models, and communicate clear, actionable findings to both technical and non-technical stakeholders. Determination of official compensation or salary relies on several different factors including, but not limited to: level of position, complexity of job responsibilities, geographic location, work experience, education, certifications, Federal Government contract labor categories, and contract wage rates.

SWIFT is a member-owned cooperative that provides the communications platform, products and services to connect more than 10,800 banking organisations, securities institutions and corporate customers in over 200 countries and territories. SWIFT enables its users to exchange automated, standardized financial information securely and reliably, thereby lowering costs, reducing operational risk and eliminating operational inefficiencies. SWIFT also brings the financial community together to work collaboratively to shape market practice, define standards and debate issues of mutual interest. SWIFT is headquartered in Belgium and has over 24 offices worldwide. In 2014 SWIFT processed more than 5.6 billion FIN messages.

Swift

25% Project Management & Team Support - Lead and manage large and complex projects and teams; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team; Serve as a technical subject matter expert (SME) for one or more data science methods, both predictive and prescriptive; Lead data science communities across several business units. 20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide technical education on advanced analytics to data science community; Partner with IT to understand potential for new tools and ways to maintain technical agility for data science; Actively seek out new business opportunities to leverage data science as a competitive advantage.

As an essential retailer to the communities we serve, our stores are open and our warehouse distribution centers are running. We’re taking measures to keep our associates safe, including:<ul><li>Providing face coverings and gloves to associates</li><li>Limiting the number of customers in stores at one time</li><li>Promoting social and physical distancing practices</li><li>Implementing additional cleaning measures to sanitize facilities</li></ul>

The Home Depot Inc

Lead Data Scientist

15% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented. Key Responsibilities: 55% Solution Development - Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies.

Data Scientist, Supply Chain Simulation and Fulfillment

15% Technical Exploration & Development- Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Build and maintain library of reusable algorithms for future use, ensuring developed codes are documented. 55% Solution Development- Design and develop algorithms and models to use against large datasets to create business insights; Participates in large data analytics project teams by serving as a technical lead for analytics projects; May lead small projects and work independently on solution development; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies.

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