United States, Michigan, Research Scientist jobs

Essential Responsibilities:

• Lead and manage data science projects, ensuring timely delivery and alignment with business goals.
• Develop and maintain data models, algorithms, and reporting systems to support data analysis and decision-making.
• Analyze complex datasets to identify trends, patterns, and insights that drive strategic initiatives.
• Collaborate with cross-functional teams to understand data needs and provide actionable insights.
• Ensure data quality and integrity through regular audits and validation processes.
• Mentor and guide junior data scientists, fostering a culture of continuous learning and improvement.

Expected Qualifications:

• 5+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• At least 7 years of experience analyzing large, multi-dimensional data sets and synthesizing insights into actionable solutions
• At least 3 years of experience in managing analytics teams
• Data driven mindset with a Master’s or Ph.D. degree in any quantitative discipline such as Analytics, Engineering, Computer Science, Economics, Statistics or Mathematics
• Experience in Advanced Analytics: Causal Inference and ML models.
• Fluent in SQL and Python
• Experience analyzing very large, complex, multi-dimensional data set
• Experience with one or multiple of the following will be highly desirable; Jupyter Notebooks, Teradata, Hadoop/Hive, BigQuery
• Domain expertise in payments or other financial services
• Exceptional communication skills, both written and verbal, to influence cross-functional teams
• Prior work experience in a product analytics space would be highly valued
• A passion for problem-solving and comfort with ambiguity

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Belonging at PayPal:

Any general requests for consideration of your skills, please

Essential Responsibilities:

• Lead the development and implementation of advanced data science models.
• Collaborate with stakeholders to understand requirements.
• Drive best practices in data science.
• Ensure data quality and integrity in all processes.
• Mentor and guide junior data scientists.
• Stay updated with the latest trends in data science.

Expected Qualifications:

• 3+ years relevant experience and a Bachelor’s degree OR Any equivalent combination of education and experience.

• Develop, refine, and implement credit risk strategies using advanced analytics and unit economics to guide smart, profitable lending decisions
• Take ownership of key performance indicators (KPIs) and metrics related to credit risk for new accounts and applications
• Monitor key portfolio metrics and segment-level performance to identify and address emerging credit risks proactively
• Partner cross-functionally with teams including Machine Learning, Fraud, Compliance, Legal, Marketing, Product, Engineering, Bank Partners, and more to align risk strategies with customer and business objectives
• Effectively communicate complex findings and strategy recommendations to both technical and non-technical audiences
• Lead end-to-end project execution with minimal assistance as a credit risk expert
• Keep up-to-date with industry trends, best practices, and emerging risks related to commercial lending

Travel Percent:

The total compensation for this practice may include an annual performance bonus (or other incentive compensation, as applicable), equity, and medical, dental, vision, and other benefits. For more information, visit .

Belonging at PayPal:

Any general requests for consideration of your skills, please

The Difference You Will Make:

You will lead the evolution of how Airbnb finds and nurtures talent across markets. You will oversee a global team of sourcers and researchers, driving a unified vision that leverages AI, data insights, and creative storytelling to build deep, diverse pipelines for both mature and emerging markets.

You will play a pivotal role in shaping our long-term talent strategy from predictive talent mapping and data-led sourcing workflows to thought leadership in how AI augments human connection in recruiting.

A Typical Day:

• Lead a high-performing global team of sourcers and talent researchers focused on Tech, Non-tech, Creative and Product disciplines.
• Partner closely with engineering, product and non technical teams, to define talent priorities and design sourcing strategies aligned with long-term business goals.
• Build and scale AI-assisted sourcing systems to automate research, outreach, and candidate matching ensuring every sourcer operates with efficiency and intelligence.
• Oversee global market intelligence, analyzing trends in emerging ecosystems (US, LATAM, EMEA, APAC) to proactively identify untapped talent markets.
• Partner with People Analytics to build predictive dashboards on talent supply, diversity insights, and competitive movement.
• Champion the evolution of candidate experience by developing personalized, high-impact engagement models that blend technology and storytelling.
• Act as a thought leader for sourcing excellence, coaching your team to think creatively, experiment with AI tools, and push the boundaries of traditional recruiting.
• Design presentations for leadership around Market Intelligence/Analysis
• Synthesize research into forecast and guidance around recruiting decision making

Your Expertise:

• 12+ years of experience in recruiting or sourcing, including 3+ years in people leadership.
• Proven success leading global teams and building scalable, data-driven sourcing strategies for high-growth organizations.
• Deep understanding of the engineering and AI/ML talent landscape, with expertise in emerging markets such as LATAM and EMEA.
• Experience leveraging AI technologies (e.g., LLMs, automation, talent intelligence platforms) to drive sourcing efficiency and insights.
• Strong analytical mindset able to interpret talent data, generate market insights, and translate them into business impact.
• Exceptional storytelling and relationship-building skills with senior business and engineering leaders. Expertise to create and deliver presentations to leadership.
• A growth mindset: curiosity, creativity, and a passion for experimenting with new ways of finding and engaging talent.

Offices: United States

Engineering Problem Solving & Innovation

• Solve complex engineering problems critical for technology and product development using software expertise and domain knowledge
• Research technological trends and collaborate with industry, academic, and standardization groups to address technology and customer challenges
• Find innovative solutions to difficult problems for midterm and long-term timeframes
• Research to define boundaries, create proof of concepts, and prototype new ideas

Manufacturing Systems Engineering

• Design and develop system-wide software solutions applying engineering, mathematical, simulation, and optimization models
• Identify and solve complex problems in factory performance, loading, equipment performance, decision science, and distribution networks
• Build, develop, validate, and apply mathematically based decision algorithms, heuristics, optimization, and simulation models
• Develop software applications of complex engineering models for manufacturing environments

Strategic Solution Development

• Work closely with business units to identify root causes and define strategic and tactical needs
• Drive appropriate business and technical software solutions using formal technical training and engineering judgment
• Develop solutions utilizing business knowledge, analytical expertise, and manufacturing domain understanding
• Lead and manage projects while influencing varying levels of customer management and decision bodies

Advanced Analytics & Modeling

• Apply discrete-event predictive modeling and digital twin manufacturing simulations
• Implement advanced analytics and machine learning techniques including regression, clustering, neural networks, and classification
• Conduct data analysis, visualization, statistical analysis, and time series analysis
• Develop optimization solutions using linear and mixed-integer programming

Core Competencies

• Excellent team, interpersonal, analysis, and presentation skills
• Ability to lead and manage complex projects
• Strong influence and communication skills across management levels
• Engineering judgment and business acumen

The Minimum qualifications are required to be initially considered for this position. Minimum qualifications listed below would be obtained through a combination of industry relevant job experience, internship experience and / orschoolwork/classes/research.The preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications

• Master of Science degree in Industrial Engineering, Operations Research, Computer Science or related quantitative field of study
• 2+ yearsof experience in discrete-event predictive modeling and digital twin manufacturing simulations
• 2+years of experience in Oracle PL/SQL, Python, R, and applied statistics

Preferred Qualifications

• Advanced Analytics experience
• Analytics and machine learning experience with regression, clustering, neural networks, and classification
• Advanced experience in data analysis, data visualization, statistical analysis, and time series analysis
• Production planning and manufacturing automation experience
• Optimization experience with CPLEX and linear/mixed-integer programming

Weoffer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here:

KEY RESPONSIBILITIES:

• Assist in the design and development of AI-driven solutions, including methods, processes, and systems for analyzing structured and unstructured data from diverse sources.
• Support machine learning model development, including data preprocessing, feature engineering, and evaluation using Python and modern AI frameworks
• Collaborate with internal stakeholders to gather requirements and translate them into AI solutions that address business needs.
• Contribute to large language model (LLM) integration, and prompt engineering for enterprise applications.
• Develop and maintain data pipelines and automation scripts for model training and deployment, leveraging SQL and Python.
• Participate in AI experimentation and prototyping, including testing new algorithms and approaches for improving performance and scalability.
• Ensure timely delivery of AI-enabled tools and insights to support decision-making and operational efficiency.

Technical Skills

• Programming & Scripting: Proficiency in Python for data preprocessing, feature engineering, and automation; basic SQL for data queries
• Machine Learning Fundamentals: Strong understanding ofsupervised/unsupervisedlearning, model evaluation, and optimization
• AI Frameworks: Exposure to TensorFlow, PyTorch, or Scikit-learn for building and testing models
• Data Analysis: Hands-on experience with Pandas, NumPy; ability to clean and manipulatestructured/unstructureddata
• Large Language Models (LLMs): Familiarity with prompt engineering and integration concepts
• Data Pipelines: Basic knowledge of ETL processes and workflow automation
• Experimentation & Prototyping: Ability to test algorithms and iterate quickly
• Cloud Concepts: Awareness of AWS/Azure/GCP for deployment (coursework or projects)
• NLP Basics: Text preprocessing, embeddings, and semantic search fundamentals

Soft Skills

• Creative Problem-Solving: Innovative approach to challenges and solution design and a passion for exploring new AI techniques and tools
• Rapid Iteration Mindset: Comfortable with fast-paced prototyping and adapting based on feedback
• Collaboration & Communication: Ability to work with cross-functional teams and explain technical concepts clearly

REQUIREMENTS/EDUCATION:

• Master's Degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, Physics, Cognitive Science or a related field.
• Exposure to large language models (LLMs), prompt engineering, or natural language processing concepts.
• Experience working with structured and unstructured data, including data cleaning and feature engineering.
• Understanding of cloud computing concepts (AWS, Azure, or GCP) through academic projects or professional experience.
• Ability to communicate in writing and through presentations and a desire to evangelize AI concepts.
• Prior internship, research, or project experience in AI, automation, or data-driven solutions is preferred.

Applications will be reviewed on a rolling basis. Please apply by January 30, 2026. Note: This position may close early based on application volume or candidate selection.

Being the cybersecurity partner of choice, protecting our digital way of life.

Your Career

As a Staff AI Scientist for Enterprise AI Solutions, you will be a critical technical leader responsible for the hands-on design, development, and implementation of AI-powered solutions that solve challenging business problems across IT and various enterprise functions (Sales, Marketing, Finance, HR, Legal, etc.). You will work closely with Principal and Distinguished Architects to translate high-level strategies into concrete AI solution designs and robust, scalable, and ethical implementations. This role demands deep technical expertise, a strong ability to solve complex problems, and a commitment to mentoring other engineers, leveraging our Enterprise AI Platform to deliver measurable business impact

Your Impact

• AI Solution Implementation: Lead the design and implementation of AI solutions, translating business problems into AI designs, and managing model selection, data requirements, and integration for AI applications.
• Platform Development: Develop and implement core components of the enterprise AI/ML platform, ensuring scalability and security. Contribute to the lifecycle of traditional and Generative AI model deployment and real-time inference systems.
• System Optimization: Design and optimize large-scale AI/ML systems for performance, reliability, and developer-friendliness, focusing on low latency and high throughput in real-time AI applications.
• Technology Adoption: Evaluate and integrate new AI tools, frameworks, and cloud solutions, aligning with architectural guidelines. Lead POCs for emerging AI innovations.
• Architectural Best Practices: Champion design standards and best practices for AI systems, guiding junior engineers.
• Technical Leadership: Mentor AI/ML engineers, lead design discussions, and perform code reviews, fostering engineering excellence.
• Cross-Functional Collaboration: Partner with Data Scientists, ML Engineers, Product Managers, and IT stakeholders to develop production-grade AI solutions.
• Responsible AI & Quality: Ensure AI systems comply with responsible AI principles and security policies. Implement automated testing and monitoring.
• Innovation & Research: Apply cutting-edge AI/ML techniques to solve problems and improve solutions, staying updated on advancements in Generative AI and LLMs.

Your Experience

• 8+ years in software engineering, with 5+ years in Data science/AI/ML experience.

• Experience deploying enterprise AI/ML systems.

• Understanding of the AI lifecycle.

• Experience with distributed systems and streaming data.

• Hands-on experience with Generative AI and LLMs.

• Proficiency in AI/ML frameworks and cloud platforms.

• Strong programming skills (Python and C++).

• Excellent communication skills.

• Masters/Bachelors degree in Computer Science or related field.

Preferred Qualifications:

• PhD degree in Computer Science , Applied Mathematics , Machine Learning or related computation field.

• Experience with open-source AI projects.

• Prior technical lead role for AI/ML projects.

• Familiarity with cybersecurity principles for AI.

What we are looking for?

• Deep Technical Expertise: Strong foundation in machine learning (theory and application), deep learning, statistical modeling, and relevant programming languages (Python, R) and libraries (TensorFlow, PyTorch, scikit-learn).

• Proven Research & Innovation: Track record of conceiving and executing novel research, publishing in top-tier conferences/journals, or delivering innovative AI solutions with significant business impact.

• System Design & Scalability: Ability to design, build, and deploy scalable and robust AI systems. Understanding of MLOps and data engineering principles.

• Problem Solving & Critical Thinking: Excellent analytical skills to tackle complex, ambiguous problems and break them down into manageable parts.

• Leadership & Mentorship: Experience in leading projects, guiding junior team members, and influencing technical direction.

• Communication & Collaboration: Ability to clearly communicate complex technical concepts to diverse audiences (technical and non-technical) and collaborate effectively with cross-functional teams.

• Business Acumen & Impact Focus: Understanding of how AI can drive business value and ability to translate research/technical work into tangible outcomes.

• Continuous Learning: Passion for staying up-to-date with the latest advancements in AI.

Compensation Disclosure

The compensation offered for this position will depend on qualifications, experience, and work location. For candidates who receive an offer at the posted level, the starting base salary (for non-sales roles) or base salary + commission target (for sales/commissioned roles) is expected to be between $165,000 - $250,000/YR. The offered compensation may also include restricted stock units and a bonus. A description of our employee benefits may be found .

All your information will be kept confidential according to EEO guidelines.