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advisor - scientific data engineer

machine learning scientist

Google

<div>
 Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act.
 
 
 Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
 
 Mountain View, OK, USA; San Francisco, CA, USA
 
 .
 
 Minimum qualifications:
 
 
 
 <ul>
 <li>
 PhD in Computer Science, Artificial Intelligence, Machine Learning, Computer Vision, or equivalent practical experience.
 </li>
 <li>
 Experience in AI research and development, including in Generative AI.
 </li>
 <li>
 Experience in Python and machine learning frameworks (e.g., Jax, TensorFlow, PyTorch).
 </li>
 <li>
 One or more accepted scientific publication submissions for conferences, journals, or public repositories (such as CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).
 
 
 </li>
 </ul>
 
 Preferred qualifications:
 
 
 
 <ul>
 <li>
 Experience in large-scale training of multimodal foundation models.
 </li>
 <li>
 Experience with Large Language Models (LLMs) and their adaptation to complex reasoning and planning.
 </li>
 <li>
 Ability to lead high-ambiguity research projects from high-level concepts to outcomes.
 </li>
 <li>
 Ability to build and scale multi-agent systems.
 
 
 </li>
 </ul>
 
 About The Job
 
 
 
 As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promising ideas quickly and broadly, managing deadlines and deliverables while applying the latest theories to develop new and improved products, processes, or technologies. From creating experiments and prototyping implementations to designing new architectures, our research scientists work on real-world problems that span the breadth of computer science, such as machine (and deep) learning, data mining, natural language processing, hardware and software performance analysis, improving compilers for mobile platforms, as well as core search and much more.
 
 
 As a Research Scientist, you'll also actively contribute to the wider research community by sharing and publishing your findings, with ideas inspired by internal projects as well as from collaborations with research programs at partner universities and technical institutes all over the world.
 
 
 EarthAI is a frontier initiative at Google Research to build the world&rsquo;s most advanced planetary foundation models and bring it together with Gemini based reasoning to understand, plan, and act to help address some of the most critical challenges of our time. Our team develops models that interpret the world's physical dynamics&mdash;from global mobility and population shifts to environmental signals&mdash;transforming the entire planet into an interactive environment for understanding and reasoning
 
 
 We are looking for a Research Scientist to push the boundaries of multimodal generative AI and agentic systems at a massive scale.
 
 
 Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we&rsquo;re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.
 
 
 The US base salary range for this full-time position is $147,000-$211,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
 
 
 Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
 
 
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Design and implement algorithms for Generative AI across massive, multimodal planet-scale datasets, including satellite streams, population understanding and global environmental signals.
 </li>
 <li>
 Lead the training and fine-tuning of Gemini models to achieve "planetary-aware" reasoning, enabling advanced task planning and multi-step execution in complex contexts.
 </li>
 <li>
 Establish new benchmarks and publish original research that pushes this field forward.
 </li>
 <li>
 Partner with cross-functional teams to deploy these models into products that promise to have a transformative impact.
 
 
 
 </li>
 </ul>
 Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
</div>

Research Scientist, Earth AI

Lyft

<div>
 At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.
 
 
 The Pricing team is a centerpiece of Lyft&rsquo;s marketplace. The Pricing team owns the models and software systems that determine the final prices shown to riders. Working with our business and analytics partners, the team owns tools to ensure Lyft offers competitive prices while making efficient financial trade-offs. Rider Engagement is a fast-growing team within Pricing, focused on developing rider-facing engagement levers and optimizing allocations and decisioning systems to drive both short term and long term business outcomes.
 
 
 As a Data Scientist specializing in Algorithms on the Rider Engagement team, you will develop mathematical models for core discounting systems and address diverse problems across optimization, prediction, machine learning, and inference. You will collaborate with cross-functional teammates and stakeholders to enhance algorithms, build and scale our rider engagement products and systems, and drive business growth. We are looking for someone who is excited about working in a fast-paced, innovative, and impactful environment, and is adept at balancing complexity and efficiency to translate real world business problems into reliable solutions and decisioning frameworks. In this role, you will report to a Data Science Manager.
 
 
 
 Responsibilities:
 
 
 
 <ul>
 <li>
 Partner with Engineers, Product Managers, and Business Partners to frame problems mathematically and within the business context
 </li>
 <li>
 Prioritize and lead deep dives into our data to uncover new product and business opportunities
 </li>
 <li>
 Be familiar with production code; collaborate with Software Engineers to implement algorithms and models in production
 </li>
 <li>
 Design, implement, and analyse different types of experiments, and facilitate and foster data-driven and informed decision making and prioritization
 </li>
 <li>
 Establish metrics that measure the health of our products, as well as rider and driver experience
 </li>
 <li>
 Drive collaboration and coordination with cross-functional teams
 </li>
 <li>
 Provide coaching and technical guidance for other teammates
 
 
 </li>
 </ul>
 
 Experience:
 
 
 
 <ul>
 <li>
 M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Computer Science, Mathematics, or other quantitative fields
 </li>
 <li>
 2+ years professional experience in a technology company setting
 </li>
 <li>
 Proven experience with building and evaluating machine learning models
 </li>
 <li>
 Proficiency with Python and working in a production coding environment
 </li>
 <li>
 Passion for solving unstructured and non-standard mathematical problems
 </li>
 <li>
 End-to-end experience with data, including querying, aggregation, analysis, and visualization
 </li>
 <li>
 Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem
 
 
 </li>
 </ul>
 
 Benefits:
 
 
 
 <ul>
 <li>
 Great medical, dental, and vision insurance options with additional programs available when enrolled
 </li>
 <li>
 Mental health benefits
 </li>
 <li>
 Family building benefits
 </li>
 <li>
 Child care and pet benefits
 </li>
 <li>
 401(k) plan with company match to help save for your future
 </li>
 <li>
 In addition to 12 observed holidays, salaried team members have discretionary paid time off, hourly team members have 15 days paid time off
 </li>
 <li>
 18 weeks of paid parental leave. Biological, adoptive, and foster parents are all eligible
 </li>
 <li>
 Subsidized commuter benefits
 </li>
 <li>
 Monthly Lyft credits and complimentary Lyft Pink membership
 
 
 </li>
 </ul>
 Lyft is an equal opportunity employer committed to an inclusive workplace that fosters belonging. All qualified applicants will receive consideration for employment without regards to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, age, genetic information, or any other basis prohibited by law. We also consider qualified applicants with criminal histories consistent with applicable federal, state and local law.
 
 
 Lyft highly values having employees working in-office to foster a collaborative work environment and company culture. This role will be in-office on a hybrid schedule &mdash; Team Members will be expected to work in the office 3 days per week on Mondays, Wednesdays, and Thursdays. Lyft considers working in the office at least 3 days per week to be an essential function of this hybrid role. Your recruiter can share more information about the various in-office perks Lyft offers. Additionally, hybrid roles have the flexibility to work from anywhere for up to 4 weeks per year. #Hybrid
 
 
 The expected base pay range for this position in the San Francisco area is $128,000 - $160,000, not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.
</div>

Data Scientist - Machine Learning, Pricing & Rider Engagement

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Join us at the Amazon's sustainability initiatives to work on environmental and social advancements to support Amazon's long term worldwide sustainability strategy. At Amazon, we're working to be the most customer-centric company on earth. To get there, we need exceptionally talented, bright, and driven people. 
 
The Worldwide Sustainability (WWS) organization capitalizes on Amazon&rsquo;s scale and speed to build a more resilient and sustainable company. We manage our social and environmental impacts globally, and drive solutions that enable our customers, businesses, and the world to become more sustainable. 
 
Sustainability Science and Innovation (SSI) is a multi-disciplinary team within WW Sustainability combining science, analytics, economics, statistics, machine learning, product development, and engineering expertise. We use data across the sustainability imperatives (carbon, water, waste, biodiversity, environmental risk and more) and these skills and capabilities to identify, develop, experiment, and scale the scientific solutions and innovations necessary for Amazon, customers and partners to help them solve their hardest unmet and evolving sustainability needs and goals. 
 
The Sustainability Science and Innovation team is looking for a Sr. Applied Scientist to collaborate closely with Economists and Environmental Scientists to build the AI/ML foundation of the future. You will define strategy and implement tooling to identify, ingest, harmonize, store, and maintain strategic models and data from both internal and external sources. 
These models and datasets must cover a wide range of topics in emerging areas and applications of AI for sustainability. This AI solutions development will support Amazon-wide sustainability initiatives like carbon footprint, climate risk monitoring, and social responsibility through the supply chain. 
 
These datasets must cover a wide range of topics such as geographic regions and data formats to unlock foundational AI research in emerging areas and applications. These solutions development will support Amazon-wide sustainability initiatives like carbon footprinting, climate risk monitoring, and social responsibility through the supply chain. 
 
If you see yourself as a hands-on leader and innovator at the intersection of AI, data, and sustainability, we'd like to connect with you. You don't necessarily have to be an expert in sustainability and climate domains. 
 
Key job responsibilities 
<ul><li>Designing, implementing, and maintaining data and AI/ML infrastructure to support a wide variety of large and complex data sets, ensuring high performance, availability, and integrity.</li><li>Identifying and solving data needs for Gen AI and foundational model training and benchmarking for tasks across the sustainability domain.</li><li>Developing and optimizing robust data pipelines for internal data from sources such as Product Lifecycle Management tools, Product Details (images, text, and structured data), Inventory Management Platforms, and financial systems.</li><li>Design and implement web-scale data collection for images, text, structured data across locations and sustainability domains.</li><li>Develop comprehensive monitoring, alarming, and data quality controls for all of the above.</li><li>Partnering with Scientists and Software Engineers to create our data collection strategy and ML Ops best practices.</li></ul> 
About the team 
Diverse Experiences: 
World Wide Sustainability values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying. 
 
Inclusive Team Culture: 
It&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (inclusive diversity) conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth: 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance: 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;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, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, San Francisco - 192,200.00 - 260,000.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, WW Sustainability

<div>Applicants in San Francisco: Qualified applications with arrest or conviction records will be considered for employment in accordance with the San Francisco Fair Chance Ordinance for Employers and the California Fair Chance Act. 
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; New York, NY, USA; San Francisco, CA, USA.<h3 class="jobSectionHeader">
Minimum qualifications:</h3><ul>
<li>Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field. 
</li>
<li>8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.</li></ul> 
<h3 class="jobSectionHeader">
Preferred qualifications:</h3><ul>
<li>10 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 8 years of work experience with a PhD degree. 
</li>
<li>Experience in scientific methodologies and in areas such as LLM.</li>
<li>Experience solving unstructured business problems with data science and translating results into impactful business/product recommendations.</li>
<li>Ability to think critically, analyze complex problems, and develop data-driven solutions.</li>
</ul><div><h2 class="jobSectionHeader">About the job</h2>
In this role, you will work on evaluation, metrics, and user insights for AI answers within Search Health. You will have opportunities to influence Product and Engineering directions through strategic data-driven insights. Furthermore, you will create and apply advanced statistical, Machine Learning (ML), and Large Language Model (LLM) methodologies to solve complex, ambiguous business problems.
In Google Search, we're reimagining what it means to search for information &ndash; any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
The US base salary range for this full-time position is $207,000-$300,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.</div><div><h2 class="jobSectionHeader">
Responsibilities</h2><ul>
<li>Research and develop advanced analysis, causal inference analysis of impact, creatve new methodologies (e.g., LLM-based method) to identify product opportunities from various data sources, product headroom analysis for key AI features. 
</li>
<li>Initiate projects inside and across the organization and drive to completion autonomously. 
</li>
<li>Frame and solve ambiguous business problems and communicate the solutions effectively. 
</li>
<li>Interact cross-functionally, be a thought partner and influence a wide range of product stakeholders. 
</li>
<li>Communicate clearly and persuasively and influence product leadership (i.e., VPs and Directors). 
</li>
</ul></div>Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.</div>

Staff Data Scientist, Research, Search Health

Genentech

<div><div><div>THE POSITION</div>
We advance science so that we all have more time with the people we love.
The Department of Cell and Tissue Genomics (CTG) is focused on developing and applying state of the art genomics technologies (e.g. single cell omics, high-content imaging, perturbations, etc) to solve key challenges in disease biology, target discovery, and translational medicine. We are seeking a highly talented, creative, and motivated computational biologist to analyze cutting-edge high-dimensional profiling and screening data, with a particular focus on high-content imaging, to decipher complex cellular circuits. The candidate will collaborate closely with members of the department to extract biological insights from diverse high dimensional data sets and support the development of new technologies, leveraging existing computational workflows and developing novel ones.
The Opportunity:
As an integral member of our dynamic team, you will be:<ul><li>
Analyzing high-content imaging data from novel technologies including optical pooled screens, spatial transcriptomics, and high-content perturbation screens, with the goal of extracting mechanistic insights into gene function and cellular phenotypes.</li><li>
Developing methods to analyze and interpret new types of perturbation data.</li><li>
Applying statistics and machine learning to investigate data and extract biological insights.</li><li>
Collaborating across diverse, cross-functional teams including experimentalists in CTG and the therapeutic areas and colleagues in the Computational Sciences Center of Excellence and the AI Biology &amp; Translation departments</li></ul>
Who You Are:<ul><li>
PhD in Computational Biology, Bioinformatics, Computer Science, or a related quantitative field. Alternatively, a PhD in molecular biology, immunology, bioengineering, etc. combined with a very strong record of data analysis, supported by publication in this area. Postdoctoral training is a plus.</li><li>
Strong publication record of biological discovery and/or methods development.</li><li>
Deep expertise in image analysis, including image processing, feature extraction, and morphological profiling. Familiarity with modern deep learning approaches (e.g., embeddings, foundation models) is a plus.</li><li>
Comfortable with the statistical principles behind current best practices in high-throughput data analysis.</li><li>
Fluent in Python and/or R.</li><li>
Excellent communication and presentation skills.</li><li>
Able to work successfully in cross-functional teams to collaboratively solve complex problems.</li><li>
Passionate about applying your analytical skills to understand health and disease.</li></ul>
Preferred Experience:<ul><li>
Experience with in situ data (FISH or ISS barcode calling).</li><li>
Familiarity with image analysis frameworks or libraries (e.g., CellProfiler).</li><li>
Experience with genomic data including single cell RNA-seq and perturbation screens is a plus.</li><li>
Experience with applying machine learning to high throughput datasets is a plus.</li></ul>
Relocation benefits are available for this posting.
The expected salary range for this position based on the primary location of California for Senior Scientist is $124,300- $230,900 and Principal Scientist is $143,200-$265,900. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.
Benefits
Genentech is an equal opportunity employer. It is our policy and practice to employ, promote, and otherwise treat any and all employees and applicants on the basis of merit, qualifications, and competence. The company's policy prohibits unlawful discrimination, including but not limited to, discrimination on the basis of Protected Veteran status, individuals with disabilities status, and consistent with all federal, state, or local laws.
If you have a disability and need an accommodation in relation to the online application process, please contact us by completing this form Accommodations for Applicants.</div>
<div><div>JOB FACTS
</div><div><div><ul><div>Job Sub Category
Research Informatics
</div><div>Schedule
Full time
</div><div>Job Type
Regular
</div><div>Posted Date
Apr 10th 2026
</div><div>Job ID
202604-108731</div></ul></div></div></div></div>

Computational Scientist 3 - Cell & Tissue Genomics

Handshake

<div>
 
 About Handshake
 
 
 
 Handshake is the career network for the AI economy. 20 million knowledge workers, 1,600 educational institutions, 1 million employers (including 100% of the Fortune 50), and every foundational AI lab trust Handshake to power career discovery, hiring, and upskilling, from freelance AI training gigs to first internships to full-time careers and beyond. This unique value is leading to unparalleled growth; in 2025, we tripled our ARR at scale.
 
 
 
 Why Join Handshake Now
 
 
 
 <ul>
 <li>
 Shape how every career evolves in the AI economy, at global scale, with impact your friends, family and peers can see and feel
 </li>
 <li>
 Work hand-in-hand with world-class AI labs, Fortune 500 partners and the world&rsquo;s top educational institutions
 </li>
 <li>
 Join a team with leadership from Scale AI, Meta, xAI, Notion, Coinbase, and Palantir, among others
 </li>
 <li>
 Build a massive, fast-growing business with billions in revenue
 
 
 </li>
 </ul>
 
 About The Role
 
 
 
 Untangling the science of Data &amp; Evaluations for Frontier AI
 
 
 Thanks to our massive network of the world&rsquo;s top experts in all domains, the demand for human data from Handshake AI has exploded (with revenue growing from 0 to well over 9-figures in the first year and growth only accelerating since). Now the world&rsquo;s top AI Labs are looking to Handshake for advice on how to leverage human expertise to make frontier models more useful for everyone, and we are forming a leading research group to advance the science of Data and Evaluations for AI.
 
 
 
 You Will
 
 
 
 <ul>
 <li>
 Publish papers, open source software, and do bleeding-edge open science on AI agents, LLMs and frontier multimodal models, RL environments, post-training.
 </li>
 <li>
 Work with all of the top AI Labs in the world and understand/shape what their researchers are prioritizing (uniquely, you get to work on research at a company whose customers are top AI researchers)
 </li>
 <li>
 Create public benchmarks that meaningfully measure AI progress, leveraging thousands of the world&rsquo;s top experts in different domains from the Handshake network to construct the most representative/high-quality benchmark.
 </li>
 <li>
 Shape the frontier of AI through high-impact research on topics that matter: how to measure/value data, how to effectively evaluate AI, what shapes of data are most effective as AI advances, what makes effective training/RL environments, post-training data recipes.
 
 
 </li>
 </ul>
 
 Desired Capabilities
 
 
 
 <ul>
 <li>
 Based in San Francisco, and excited to work in the office.
 </li>
 <li>
 Ph.D. in ML/AI, data science, or related fields.
 </li>
 <li>
 Publications in top AI/ML venues like NeurIPS, ICML, ICLR.
 </li>
 <li>
 Builders who love to tinker with LLMs/Agents and ship high-quality software, benchmarks/datasets, research, blogs.
 
 
 </li>
 </ul>
 
 Perks
 
 
 
 Handshake delivers benefits that help you feel supported&mdash;and thrive at work and in life.
 
 
 
 
 The below benefits are for full-time US employees.
 
 
 
 
 🎯
 
 Ownership:
 
 Equity in a fast-growing company
 
 
 💰
 
 Financial Wellness
 
 : 401(k) match, competitive compensation, financial coaching
 
 
 🍼
 
 Family Support:
 
 Paid parental leave, fertility benefits, parental coaching
 
 
 💝
 
 Wellbeing:
 
 Medical, dental, and vision, mental health support, $500 wellness stipend
 
 
 📚
 
 Growth:
 
 $2,000 learning stipend, ongoing development
 
 
 💻
 
 Remote &amp; Office:
 
 Internet, commuting, and free lunch/gym in our SF office
 
 
 🏝
 
 Time Off:
 
 Flexible PTO, 15 holidays + 2 flex days, winter #ShakeBreak where our whole office closes for a week!
 
 
 🤝
 
 Connection:
 
 Team outings &amp; referral bonuses
 
 
 Explore our mission, values, and comprehensive US benefits at joinhandshake.com/careers.
 
 
 Compensation Range: $320K - $365K
 
 
</div>

AI Research Scientist

Uber

<div>About the Role
 
 
We're looking for a data scientist to join Uber's Account Actioning Data Science team to provide data expertise to ensure that our policies on gaining and maintaining access to the Uber platform are transparent and fair. This will be a highly cross-functional role that will work closely with operations, engineering, product management, and partner data teams. You will build out and own product and operations metrics, provide key insights, conduct deep dive analysis to understand new opportunities and present findings, and work with cross-functional partners on coming up with new policy and product solutions while measuring impact. You will play an influential role in helping drive critical product and policy decisions.
 
 
What the Candidate Will Need / Bonus Points
- What the Candidate Will Do - 
 
 
<ul><li>Refine ambiguous questions and generate new hypotheses about the product and business through a deep understanding of the data, our customers, and our business.
</li><li>Define how our teams measure success, by developing Key Performance Indicators and other user/business metrics, in close partnership with Product and other subject areas such as engineering, operations and marketing.
</li><li>Collaborate with data scientists and engineers to build and improve on the availability, integrity, accuracy, and reliability of data logging and data pipelines.
</li><li>Develop data-driven business insights and work with cross-functional partners to identify opportunities and recommend prioritization of product, growth, and optimization initiatives.
</li></ul>- Basic Qualifications - 
 
 
<ul><li>3+ years proven experience in product analytics or ontological data modeling.
</li><li>M.S. or Bachelors degree in Math, Economics, Bioinformatics, Statistics, Engineering, Computer Science, or other quantitative fields.
</li><li>Advanced SQL and Python expertise.
</li><li>Basic understanding of experimental design (such as A/B experiments) and statistical methods.
</li><li>Ability and experience in extracting insights from data, and summarizing learnings / takeaways.
</li><li>Experience with Excel and some dashboarding/data visualization (i.e. Tableau, Mixpanel, Looker, or similar).
</li><li>Excellent judgment, critical-thinking, and decision-making skills.
</li><li>Balance attention to detail with swift execution.
</li></ul>- Preferred Qualifications - 
 
 
<ul><li>Advanced degrees in Math, Economics, Statistics, Engineering, Computer Science, Operation Research, Machine Learning or other quantitative fields.
</li><li>4+ years industry experience in consumer facing product analytics.
</li><li>Strong storytelling: distill interesting and hard-to-find insights into a compelling, concise data story.
</li><li>Ability to communicate effectively and manage relationships with partners coming from both technical and non-technical backgrounds.
</li>Ability to solve complex business problems that cross multiple product/project areas and teams. 
<li>
</li></ul> 
 
For San Francisco, CA-based roles: The base salary range for this role is USD$142,000 per year - USD$158,000 per year. You will be eligible to participate in Uber's bonus program, and may be offered an equity award &amp; other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits. More details can be found at the following link https://jobs.uber.com/en/benefits.</div>

Data Scientist II

Explore 116+ Machine learning scientist in San Francisco this April. Find roles across top companies and apply now to boost your career.