Staff Applied Scientist Job at Range (McLean)

Member of Technical Staff, Applied Scientist

As Microsoft continues to push the boundaries of AI, we are on the lookout for p...

Location

United States , Mountain View

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
3+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).
Experience presenting at conferences or other events in the outside research/industry community as an invited speaker.
3+ years experience conducting research as part of a research program (in academic or industry settings).
1+ year(s) experience developing and deploying live production systems, as part of a product team.
1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping.

Job Responsibility

Develop and refine data pipelines and infrastructure to support AI model development for Copilot.
Collaborate with research teams to integrate cutting-edge AI advancements into production systems.
Design, train, and evaluate machine learning models, ensuring performance optimization and scalability.
Work closely with engineering and product teams to ensure AI-driven experiences meet quality and user experience standards.
Conduct rigorous data analysis and experimentation, leveraging insights to improve Copilot’s intelligence.
Overcome obstacles to deliver iterative improvements in AI performance and responsiveness.
Stay ahead of the latest innovations in deep learning, reinforcement learning, and generative AI.

Member of Technical Staff, Applied Scientist

We’re seeking a Member of Technical Staff – Applied Scientist to help design and...

Location

United States , Mountain View

Salary:

119800.00 - 258000.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
Experience prompting, evaluating, and working with large language models
Experience writing production-quality Python code

Job Responsibility

Architect and implement advanced Copilot features such as Deep Research and Web artifact generation
Lead evaluation efforts of models deployed within Copilot, ensuring performance aligns with product goals
Design scalable systems that leverage large language models (LLMs) to deliver intelligent, user-facing experiences
Develop evaluation frameworks and metrics to assess feature performance and user impact
Conduct thorough reviews of data analysis and techniques to identify gaps and areas for re-examination
Build data collection pipelines to support prompt engineering and fine-tuning of LLMs
Track advances in industry and academia, identify relevant state-of-the-art research, and adapt algorithms to drive innovation
Train and optimize content classifiers to enable context-aware interactions within Copilot
Independently write efficient, readable, and extensible code and model pipelines
Contribute to defining the model quality roadmap for Copilot, balancing technical rigor with business and product priorities

Fulltime

Staff Applied Scientist - Credit Underwriting

As an Applied Scientist at OnePay, you’ll focus on building advanced credit and ...

Location

United States

Salary:

170000.00 - 230000.00 USD / Year

OnePay

Expiration Date

Until further notice

Requirements

5+ years of experience building and deploying machine learning or statistical models in credit risk, lending, or financial services
Proven expertise in credit scoring, underwriting, or loss forecasting using large-scale structured and behavioral data
Strong technical foundation in Python, SQL, and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) with a deep understanding of model development and evaluation pipelines
Experience translating complex modeling insights into actionable business and product decisions, collaborating closely with Product, Engineering, and Analytics teams.
Familiarity with model governance, explainability, and fairness in credit decisioning and regulatory contexts (ECOA, FCRA, etc.)
Fluency in collaborating with Product, Engineering, and Analytics teams to bring AI/ML solutions from ideation to deployment.
Drive and proactivity – everyone here is a builder and executor.

Job Responsibility

Develop and deploy real time credit scoring and risk assessment models that optimize lending decisions and expand credit access for underbanked customers.
Leverage machine learning, statistical, and behavioral modeling to predict repayment patterns, creditworthiness, and affordability with fairness and transparency.
Partner with Product and Engineering to integrate credit models into production systems powering products like OnePay Advance and other lending initiatives.
Collaborate with Analytics, Product, and Engineering teams to monitor performance, manage model drift, and ensure responsible AI and regulatory alignment.
Experiment with innovative modeling techniques—including alternative data, LLM-assisted feature engineering, and explainable AI—to continuously enhance OnePay’s credit capabilities

What we offer

Competitive base salary, stock options, and health benefits from Day 1
401(k) plan with company match
Remote-friendly (US), flexible time off (FTO), and opportunities for growth
A high-growth, mission-driven, inclusive culture where your work has real impact

Fulltime

Member of Technical Staff, Applied Scientist - Windows Copilot

The Windows Copilot team is at the forefront of redefining how AI enhances every...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research) OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience.
Proven track record of deploying machine learning models in large-scale production environments.
9+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows.
4+ years of experience building data pipelines, training deep learning models, and optimizing AI workflows.

Job Responsibility

Develop and refine data pipelines and infrastructure to support AI model development for Copilot.
Collaborate with research teams to integrate cutting-edge AI advancements into production systems.
Design, train, and evaluate machine learning models, ensuring performance optimization and scalability.
Work closely with engineering and product teams to ensure AI-driven experiences meet quality and user experience standards.
Conduct rigorous data analysis and experimentation, leveraging insights to improve Copilot’s intelligence.
Overcome obstacles to deliver iterative improvements in AI performance and responsiveness.
Stay ahead of the latest innovations in deep learning, reinforcement learning, and generative AI.
Embody our Culture and Values.

Fulltime

Staff Applied Research Scientist - Martech AI

We are seeking a highly experienced and strategic Staff Applied Research Scienti...

Location

United States , New York City; Palo Alto; Chevy Chase; Dallas; Seattle; Chicago; Austin

Salary:

130000.00 - 260000.00 USD / Year

Geico

Expiration Date

Until further notice

Requirements

BS in Computer Science, Machine Learning, Statistics, Mathematics, or a related quantitative field, PhD is preferred
At least 6+ years of professional experience delivering applied AI/ML solutions in production, including leading cross-functional initiatives with enterprise impact
Demonstrated ability to leverage LLMs and agentic AI systems to develop and deploy personalized marketing solutions, including individualized content generation, campaign targeting, and optimization of customer engagement/retention/conversion strategies
Strong proficiency in Python and SQL
deep experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn
Demonstrated experience establishing KPI frameworks, experimentation, and causal analysis to quantify model impact and inform prioritization
Excellent stakeholder management skills with a track record of driving alignment and adoption across product, engineering, and business teams
Strong written and verbal communication skills
ability to set the right context and explain complex technical topics to varied audiences, including executives

Job Responsibility

Identify High-Impact Opportunities: Proactively surface and shape high-value AI/ML initiatives by engaging with product, engineering, and operations to align technical roadmaps with strategic business goals
Architecture & Technical Direction: Provide architectural leadership for AI/ML solutions impacting multiple stakeholders. Establish standards for scalability, reliability, observability, compliance, and cost efficiency across online and batch systems
Development & Productionization: Lead end-to-end delivery of AI/ML solutions, including model design, data pipelines, feature stores, evaluation, deployment, A/B testing, and monitoring in real-time and batch environments. Ensure clear plans, milestones, and on-time delivery
ROI Measurement & Experimentation: Establish robust mechanisms to quantify business impact, including KPI definition, experimentation frameworks, and causal inference approaches to guide decision-making and prioritize investments
Innovation & Research Integration: Stay current with cutting-edge research in ML, GenAI, and optimization. Prototype and harden novel techniques that push the boundaries of innovation within GEICO’s insurance ecosystem
Set technical direction for multi-quarter research initiatives
build evaluation frameworks, ensure reproducibility/responsible AI, and drive cross-functional adoption
shepherd patents
Cross-Functional Collaboration: Champion collaboration across Product, Engineering, Data Platform, Governance, Legal, and Operations to ensure responsible, compliant, and effective adoption of AI systems
Mentorship & Capability Building: Mentor junior and senior scientists, elevate technical standards (coding, testing, documentation, reproducibility), and foster a culture of scientific rigor and engineering excellence

What we offer

Comprehensive Total Rewards program that offers personalized coverage tailor-made for you and your family’s overall well-being
Financial benefits including market-competitive compensation
a 401K savings plan vested from day one that offers a 6% match
performance and recognition-based incentives
and tuition assistance
Access to additional benefits like mental healthcare as well as fertility and adoption assistance
Supports flexibility- We provide workplace flexibility as well as our GEICO Flex program, which offers the ability to work from anywhere in the US for up to four weeks per year

Fulltime

Staff ML Validation Applied Scientist

As a Staff ML Validation Applied Scientist on the Software Validation team withi...

Location

United States , Sunnyvale

Salary:

218800.00 - 335300.00 USD / Year

General Motors

Expiration Date

Until further notice

Requirements

8+ years of experience and MS/PhD in Computer Science, Machine Learning, Robotics, Software Engineering, Data Science, or a related field
Strong proficiency in Python and at least one systems language (e.g., C++), with experience building production systems over large datasets
Deep understanding of and experience evaluating modern ML for robotic systems
Hands-on experience using AI agents, LLM-based tools, or workflow orchestration to automate parts of the development, validation, or operations lifecycle
Demonstrated ability to design and implement behavioral and ML metrics and associated tooling for validation and regression detection of complex ML systems
Strong analytical skills and systems thinking
able to reason about complex AV behavior and ML model interactions and turn insights into code and tools
Effective communicator who can work across teams and provide technical leadership and mentorship to other engineers and researchers

Job Responsibility

Lead ML-centric validation strategy for deep learning components across perception, prediction, and planning in AV, defining evaluation methodologies with cross-functional partners
Build AI validation critics and agentic acceleration workflows using LLM- and model-based agents plus orchestration to automate scenario review, anomaly detection, and end-to-end validation flows
Prototype ML research into scalable tools by transforming ML research into performant tools integrated into CI/CD and large-scale pipelines, owning key behavior and ML validation services and data pipelines
Drive simulation-based ML evaluation at scale by evaluating deep learning modules in realistic sensor and traffic simulation and expanding behavioral and scenario coverage tightly linked to ML models
Provide cross-functional collaboration and leadership across Simulation, Safety, Systems Engineering, Autonomy, and tools teams through reviews, roadmapping, standards, and mentorship focused on high-quality, automation-first software

What we offer

medical
dental
vision
Health Savings Account
Flexible Spending Accounts
retirement savings plan
sickness and accident benefits
life insurance
paid vacation & holidays
tuition assistance programs

Fulltime

Staff Scientist, Tech

We are looking for a Staff Scientist (L5B) with deep expertise in Operations Res...

Location

India , Bangalore

Salary:

Not provided

Uber

Expiration Date

Until further notice

Requirements

Undergraduate or graduate degree in Operations Research, Applied Mathematics, Computer Science, or related quantitative field.
9+ years of industry experience applying optimization, operations research, or algorithmic decision science in real-world systems.
Strong experience developing and implementing optimization models (LP, MIP, stochastic optimization, etc.).
Proficiency in Python and SQL, and familiarity with optimization tools and libraries
Experience collaborating with Engineering teams to deploy algorithms in production systems.

Job Responsibility

Develop optimization models for Marketplace Problem
Identify opportunities where optimization techniques can improve marketplace balance, driver utilization, and rider experience.
Design optimization models to solve complex marketplace problems such as dispatch optimization, driver repositioning, and pricing optimization.
Translate business problems into mathematical optimization formulations (e.g., linear programming, mixed-integer programming, network flow models etc.).
Build Scalable decision systems
Develop scalable optimization algorithms capable of operating in large-scale, real-time environments.
Work closely with Engineering to productionize optimization models and ensure they integrate effectively with Uber's systems.
Build & lead the execution of the technical roadmap for the charters
Mentor scientists on optimization modeling, algorithm design, and decision science methodologies.
Establish best practices for translating theoretical optimization methods into production-ready systems.

What we offer

Accommodations may be available based on religious and/or medical conditions, or as required by applicable law

Fulltime

Staff Scientist - Reservations

The Reservations data science team owns the experience and algorithms powering t...

Location

United States , Seattle

Salary:

216000.00 - 240000.00 USD / Year

Uber

Expiration Date

Until further notice

Requirements

Ph.D., M.S. or Bachelor's degree in Statistics, Economics, Mathemathics, Computer Science, Machine Learning, Operations Research, or other quantitative fields.
6+ years of industry experience as an Applied or Data Scientist or equivalent.
Proficiency in programming languages (Python, Java, Scala) and ML frameworks (TensorFlow, PyTorch, Scikit-Learn), underpinned by a solid grasp of MLOps practices, including design documentation, testing, and source code management with Git.
Agile project management capabilities, adept at using tools like JIRA, and a driven problem-solver with a passion for impacting the retail sector at scale.
Advanced skills in the development and deployment of large-scale ML models
Experience in experimental design and analysis (e.g., A/B and market-level experiments), causal inference.
Strong business and product sense: delight in shaping vague questions into well-defined analyses and success metrics that drive business decisions.
Strong experience in causal inference, optimization, and machine learning.
Experience in algorithm development and prototyping. Particularly in Pricing domain.
Ability to drive clarity on the best modeling or analytic solution for a business objective

Job Responsibility

Deploy a wide variety of methodologies, including causal inference techniques, funnel analyses, and econometric modeling to identify our largest business opportunities.
Work together with Product, Operations, and Engineering partners to design a roadmap of features and initiatives as well as the long-term team strategy.
Run large scale experiments to validate the impact of new features.
Present findings to business and executive audiences

What we offer

Bonus program
Equity award
401(k) plan

Fulltime

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