Data Scientist, Safety Job at Uber (San Francisco)

Staff Safety Data Scientist, Safety Analysis

We are searching for a Staff Safety Data Scientist on the Safety Analysis team w...

Location

United States , Pittsburgh

Salary:

Not provided

Aurora Innovation

Expiration Date

Until further notice

Requirements

Bachelor's degree in Data Science, Statistics, Mathematics, Physics, Engineering, Computer Science, or equivalent applicable technical experience
7+ years of progressive experience solving large-scale complex problems
Demonstrated experience in a safety related domain (e.g., transportation, aerospace, robotics, medical devices)
Strong understanding of safety principles and risk assessment methodologies
with a proven track record of using data science techniques to solve safety challenges and mitigate risks in a dynamic environment
Deep command of statistical methods, probabilistic modeling, and performing rapid exploratory data analysis
Expertise in data science tools (e.g., Python, SQL, R), statistical modeling, machine learning, predictive analytics, and visualization software (e.g., Tableau, Power BI)
Adept at querying, analyzing, and visualizing large datasets
Excellent communication and presentation skills, with the ability to convey complex information to various audiences
Strong leadership skills, with the ability to provide guidance and mentorship

Job Responsibility

Lead the development of novel quantitative data analytics using both proprietary (Aurora-logged, sensor, system, integration testing data) and publicly available data (CRSS, FARS, state-level information)
Author and present technical analyses and findings to diverse internal and external audiences, including stakeholders, authoritative bodies, and industry forums
Design and automate data collection and analysis to support ongoing safety programs
Extract insights from historical system safety performance to develop leading indicators for future performance forecasting
Analyze safety data from operational vehicles, crash metrics, and near-miss incidents to inform safety strategies and decision-making
Develop statistical models and algorithms to predict potential risks and prevent incidents, improving the safety performance of autonomous systems
Model self-driving vehicle behaviors at the system and subsystem levels
Develop and maintain reports and expressions of baseline risk coverage and application in operations
Design and develop expressions of risk benchmarking from similar industries
Create dashboards and reports for communicating risk, ranking, and anomalies

What we offer

annual bonus
equity compensation

Fulltime

New

Data Scientist

WHAT'S IN IT FOR YOU Benefits: Compensation: $88,000 - $121,000 Annual Performan...

Location

Canada , Cambridge

Salary:

88000.00 - 121000.00 USD / Year

ATS Automation Tooling Systems Inc.

Expiration Date

Until further notice

Requirements

A post-secondary engineering degree, diploma or equivalent in a quantitative field (Computer Science, Information system, Mathematic, Statistics, Machine Learning, Artificial intelligence, Engineering)
A Master’s degree is considered beneficial
Strong experience with the deployment, configuration, and operationalization of Databricks environments, including workspace architecture, cluster management, CI/CD integration, security, governance, and enterprise-scale administration
Experienced in building and managing modern data pipelines and lakehouse architectures using Delta Lake, Delta Live Tables, Structured Streaming, Workflows, medallion architectures (Bronze/Silver/Gold), and real-time/batch ingestion frameworks
Deep understanding of Databricks ecosystem components including Unity Catalog, data lineage, RBAC, monitoring/observability, cost optimization, ML/AI enablement, model serving, and secure enterprise data collaboration through Clean Rooms
Proven experience integrating Databricks with enterprise cloud and industrial data ecosystems, including Kafka, SQL databases, APIs, IoT/OT platforms, and cloud environments such as Azure, AWS, and GCP
Strong understanding of scalable data engineering, governance, multi-tenant architectures, and enterprise data platform strategies supporting analytics, AI, and operational intelligence initiatives
Proficiency in programming languages like Python, R, or Java
Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy)
Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)

What we offer

Compensation: $88,000 - $121,000
Annual Performance-Based Incentive Bonus
5% RRSP match
Stock purchase plan
Starting 3 weeks of vacation
Benefits package (health and dental) + $600 health spending account
Half-Day Fridays
Continuous learning and career growth with global mobility opportunities
A chance to contribute to something bigger - advancing the future of healthcare through automation

Fulltime

Clinical Safety Scientist

Location

United Kingdom , London

Salary:

350.00 - 500.00 GBP / Day

SRG

Expiration Date

Until further notice

Requirements

Degree (BSc or higher) in Biomedical Sciences, Life Sciences, or related healthcare field
Proven experience in clinical trial data review and pharmacovigilance activities
Strong scientific writing skills with experience in regulatory safety documents
Knowledge of signal detection, causality assessment, and safety data evaluation
Experience in literature review, data analysis, and interpretation
Understanding of pharmacovigilance regulations and drug development processes (HIV knowledge advantageous)

Job Responsibility

Monitor and evaluate the safety profiles of assigned products across development and post-marketing phases
Conduct signal detection and evaluation, including analysis of safety data and literature review
Contribute to the development and maintenance of Risk Management Plans and regulatory safety documentation
Support preparation of key regulatory deliverables (e.g., DSURs, PBRERs, EU RMPs, licence renewals)
Collaborate with safety physicians on benefit-risk assessments and individual case safety reviews
Ensure all safety documentation meets global regulatory and compliance standards

Senior Data Scientist, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , Bay Area

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

Senior Data Scientist - Agentic Systems

The Global Marketing Engines and Experiences (E&E) team within Microsoft is resp...

Location

United States , Redmond

Salary:

119800.00 - 234700.00 USD / Year

Microsoft Corporation

Expiration Date

Until further notice

Requirements

Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
OR equivalent experience

Job Responsibility

AI-Native Operations
Design, build, and ship agentic capabilities that make the analytics team more AI-native, including co-PM agents that triage incoming work, monitor data science workstreams in Azure DevOps, and propose ticket updates that keep our backlog accurate without manual hygiene effort
Build PM-layer agents that read across the Azure Dev Ops (ADO) portfolio to surface risk, estimate effort on new requests, and recommend project plans that managers can adapt rather than write from scratch
Establish shared infrastructure and patterns — prompting, evaluation, orchestration, observability, guardrails — that let the rest of the team build downstream agents reliably
Analyst Delivery Acceleration
Develop LLM-powered internal tools and skills that compress the cycle from analytics request to delivered insight, including capabilities that draft, format, and pressure-test the standard inputs analysts produce for MBR, MMR, and leadership review rhythms
Identify the highest-friction parts of the analyst delivery flow and design generative AI interventions that remove rather than relocate the work
Partner with the analytics team to instrument adoption, measure time saved, and iterate based on real usage rather than projected value
Marketer-Facing Capabilities
Lead the design and delivery of marketer-facing generative AI capabilities, anchored by a conversational analytics agent that allows marketers across Brand, Product Marketing Management (PMM), Customer Insights, and demand generation to self-serve on the analytics questions they bring to the team today

What we offer

Eligible for benefits and other compensation

Fulltime

Data Scientist

Amazon Quick Suite is an enterprise AI platform that transforms how organization...

Location

United States , Seattle; Santa Clara; New York

Salary:

136000.00 - 212800.00 USD / Year

Amazon Pforzheim GmbH

Expiration Date

Until further notice

Requirements

2+ years of data scientist experience
3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
1+ years of working with or evaluating AI systems experience
1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience
Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Experience applying theoretical models in an applied environment

Job Responsibility

Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features
Leverage LLMs for synthetic data corpora generation
data evaluation and quality assessment using LLM-as-a-judge settings
Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases
Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance
Develop and refine annotation guidelines and quality frameworks for evaluation tasks
Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies
Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements
Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts
Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets

What we offer

health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage)
401(k) matching
paid time off
parental leave
sign-on payments
restricted stock units (RSUs)

Fulltime

Senior Data Scientist

You will join a team of data scientists developing the next generation of Genius...

Location

United Kingdom , London

Salary:

Not provided

Genius Sports

Expiration Date

Until further notice

Requirements

A BSc, MSc or PhD in Data Science, Mathematics, Computer Science, Computational Statistics, Machine Learning or other STEM subject
Expert understanding of probability and statistics fundamentals
Proficiency with Python or other scripting/programming languages (R, Matlab, etc)
Expertise in a broad range of data science / machine learning algorithms (Monte Carlo simulation, neural networks, logistic regression, random forest, etc.) with a proven track record of delivering solutions to complex problems
Ability to bring clarity to complex domains, rapidly developing a deep understanding and challenging unclear requirements
Mentoring of other team members, helping them develop their skills and deliver effectively
Curiosity and strong desire to learn and improve
Social skills, being able to act as a facilitator, can balance enabling others with individual contributions
Time management and asynchronous communication skills relevant for a geographically diverse engineering organization
Enthusiasm and ability to work collaboratively within a team

Job Responsibility

Join a team of data scientists developing the next generation of Genius Sports’ market leading sports models
Prototype, implement, evaluate and optimize algorithms to calculate the probabilities of sporting outcomes
Play a major role in developing and implementing predictive models across all major sporting codes
Join a specially formed, highly skilled team delivering an innovative & intelligent product
Form part of a multi-disciplinary Agile team of Software Engineers, Data Scientists, QA Engineers and a Product Manager
Work closely to the fundamental principles of continuous delivery and empowered, high-performing teams
Operate in a squad model to allow focus on the business top priorities
Collaborate with high calibre engineers and deliver smart solutions with an autonomous & performance focused approach

What we offer

Competitive salary and range of benefits
Committed to supporting employee wellbeing and helping you grow your skills, experience and career

Fulltime

Senior Data Scientist, AI & Model Risk

It all started with an idea at Block in 2013. Initially built to take the pain o...

Location

United States , New York

Salary:

139000.00 - 225000.00 USD / Year

Cash App

Expiration Date

Until further notice

Requirements

A minimum of 5 years of related experience with a Bachelor’s degree in a quantitative field
or 3 years and a Master’s degree
or a PhD without experience
or equivalent work experience in risk management, model risk management, or AI risk management
Proficiency in Python or similar languages for evaluating AI system behavior, writing test scripts, or analyzing model outputs
Strong understanding of generative AI architectures
Including LLMs, transformer models, RAG systems, and agentic AI, plus hands-on experience interacting with and critically evaluating these systems, sufficient to assess design decisions, output quality, and limitations
Understanding of interagency model risk management principles, including SR 26-2
Knowledge of AI testing methodologies, ex. functional testing, bias testing, adversarial testing, and performance monitoring plus familiarity with data privacy and security principles (encryption, access controls, data classification)
Excellent written and verbal communication and the ability to translate complex technical AI concepts for non-technical stakeholders, senior management, and regulators

Job Responsibility

Lead end-to-end AI Risk Assessments for generative AI and LLM use cases across the Bank
Embedding in Block's enterprise-wide GenAI review process, coordinating cross-functional SMEs (Legal, Compliance, InfoSec, Data Governance, MRM, ERM, BRC, TPRM, Financial Crimes), and managing timelines to ensure reviews are completed within SLA
Review AI system design and documentation
Including retrieval sources, assumptions, limitations, fallback plans, guardrail configurations, and change management procedures — across banking use cases such as fraud detection, BSA/AML compliance, credit decisioning, and customer-facing applications, ensuring governance controls are commensurate with each use case's risk profile
Assess pre-deployment testing for adequacy inclusive of output integrity, hallucination detection, boundary and edge case testing, ethical and safety guardrails, bias testing, A/B testing, volume testing, and UAT — designing and conducting independent testing as needed
Evaluate ongoing monitoring plans for comprehensiveness - including accuracy, hallucination rates, drift detection, sensitive data controls, reliability metrics, CSAT, acceptable performance ranges, and documented remediation procedures
Develop and maintain templates, tools, and procedures to support the effectiveness and scalability of the AI Risk Governance Program
Monitor the evolving regulatory landscape for AI in banking — including FFIEC IT Examination Handbook standards, FDIC Financial Institution Letters, interagency statements, and the anticipated RFI on AI model risk management referenced in SR 26-2 — and incorporate emerging guidance into the AI risk governance program
support SFS's response to regulatory inquiries as needed

What we offer

Remote work
medical insurance
flexible time off
retirement savings plans
modern family planning

Fulltime

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Data Scientist, Safety

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