Design and implement machine learning–driven bidding algorithms for Netflix’s ad tech ecosystem.
Compensation
The range for this role is $500,000.00 - $860,000.00. This compensation range will vary based on location.
Responsibilities
Design and implement machine learning–driven bidding algorithms that optimize ad performance against objectives such as Clicks, Conversions, CPA and ROAS.
Build, train, and evaluate bidding algorithms on large-scale production data, ensuring robustness to marketplace dynamics, seasonality, and distribution shifts.
Develop online and offline evaluation frameworks to rigorously measure the impact of bidding algorithms and policy changes.
Inform and influence auction and pricing mechanism design, ensuring alignment between bidding algorithms, marketplace efficiency, and business goals.
Partner closely with the product team to define bidding objectives, constraints, and trade-offs that align with product and revenue goals.
Requirements
Advanced degree (PhD or Master’s) in Computer Science, Statistics, Mathematics, or related quantitative field
Apply machine learning and information retrieval methods to enterprise search problems within the Copilot Agents & Search Quality team.
Compensation
The typical base pay range for this role across the U.S. is USD $102,100 - $202,200 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $133,800 - $219,200 per year.
Responsibilities
Investigate search and retrieval quality problems using data, offline evaluation, and statistical analysis.
Develop and test methods for query understanding and sparse, dense, or multimodal retrieval, including large language model techniques where appropriate.
Build and analyze evaluations and experiments; explain results, limitations, and recommendations to partners.
Collaborate with engineering and product teams to integrate validated approaches and assess quality, latency, and efficiency.
Document findings and refine solutions based on evaluation results and product needs.
Requirements
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
Nice to have: Information retrieval or search relevance
Lead high-impact analytical projects, develop AI-powered solutions, and translate insights into actionable business recommendations for Microsoft sellers and leaders.
Compensation
Data Science IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200 - $261,000 per year.
Responsibilities
Own ambiguous, high-impact analytical problems from definition through deployment and adoption
Identify and integrate relevant data sources
Define analytical approaches and success criteria
Develop statistical, machine learning, and AI-powered solutions
Translate findings into clear recommendations for business and technical leaders
Requirements
Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
The Senior Data Scientist will analyze large and complex datasets from Caterpillar’s connected field assets to identify trends, opportunities, and insights that create business and customer value. This role will focus on turning machine and connectivity data into meaningful, actionable recommendations that support better decision-making across the organization.
Compensation
Summary Pay Range:
$112,710.00 - $183,140.00
Responsibilities
Analyze data from Caterpillar’s connected field assets to identify machine usage trends, performance issues, and opportunities to improve customer outcomes.
Develop insights that help dealer- and customer-facing teams proactively identify equipment issues and make more informed recommendations.
Turn connectivity and machine data into actionable business insights, rather than simply reporting or passing along data.
Partner across Construction Industries, Resource Industries, and Power & Energy to address real-world equipment and fleet challenges using connected asset data.
Develop analytical models and data-driven solutions that support condition monitoring, fleet management, and improved product and service decisions.
Requirements
Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related technical field
Nice to have: Agentic AI
Nice to have: AI agents
Nice to have: autonomous AI workflows
Nice to have: IoT
Introduction to Bioinformatics, Department of Applied Sciences and Professional Studies - Adjunct Faculty
University of Maryland Global Campus · Posted Nov 12, 2026
Adjunct Faculty to teach Introduction to Bioinformatics (BIOT 630), emphasizing data interpretation, sequence analysis, and mathematical modeling, while mentoring students in an asynchronous online format.
Compensation
Instructor: No Terminal Degree: Step 1 $806 - Step 11 $1,050 per credit hour
Assistant Adjunct Professor: No Terminal Degree Step 1 $877 - Step 11 $1,127 per credit hour
Assistant Adjunct Professor: Terminal Degree Step 1 $1,023 - Step 11 $1,288 per credit hour
Associate Adjunct Professor: No Terminal Degree Step 1 $947 - Step 11 $1,205 per credit hour
Associate Adjunct Professor: Terminal Degree Step 1 $1,202 - Step 11 $1,483 per credit hour
Adjunct Professor: No Terminal Degree Step 1 $1,023 - Step 11 $1,288 per credit hour
Adjunct Professor: Terminal Degree Step 1 $1,347 - Step 11 $1,645 per credit hour
Responsibilities
Maintain an active classroom presence at least 5 days per week
Bridge theory & practice with real-world expertise
Foster an inclusive, culturally responsive environment
Respond to inquiries and return feedback consistently
Monitor student progress and conduct proactive outreach
Requirements
Terminal degree in Biotechnology, Molecular Biology, or related field from an accredited institution of higher learning
Nice to have: Teaching adult learners in an online, asynchronous environment
Nice to have: Prior postsecondary teaching experience
Nice to have: Active engagement in discipline's professional community
Partner closely with computational and medicinal chemists on Discovery Chemistry project teams to address challenging structure-activity relationships and multi-parameter optimization
Develop and deploy specialized informatics workflows for non-traditional modalities (cyclic peptides, macrocycles) and DNA-Encoded Library platforms, including combinatorial enumeration, selection data triage, and hit prioritization
Design, validate, and implement scalable cheminformatics and machine learning pipelines for predictive property modeling, virtual screening, and chemical library triage
Establish robust, automated computational tools and data pipelines that bridge internal chemical data platforms and modern modeling frameworks
Maintain an active external scientific presence through publications, conference presentations, and community engagement, while mentoring junior staff, interns, and co-ops
Requirements
Ph.D. in Cheminformatics, Computational Chemistry, Chemistry, Computer Science, Bioinformatics, or a related quantitative discipline
M.S. degree with 4+ years of relevant industry/research experience
Nice to have: computational design of cyclic peptides
A technology and product leader with 15+ years of banking and financial services experience, combining deep expertise in data, ML, AI, cloud technology, product management, regulatory reporting, and financial analytics.
Compensation
New York / New Jersey: $ 150-188K
Non–New York / New Jersey: $137-169 K
depending on job-related knowledge, skills, experience and location. This role may also be eligible for certain discretionary performance-based bonus and/or incentive compensation.
Responsibilities
Lead the end-to-end product lifecycle, from business discovery and requirements through architecture, development, production deployment, adoption, and continuous improvement
Design scalable backend data and AI platforms supporting commercial banking, risk, finance, operations, and enterprise data use cases
Develop and scale AI-powered products using technologies such as LLMs, RAG, natural-language-to-SQL, AI agents, and intelligent automation to improve operational processes and information delivery for management, sales and regulatory reporting
Partner with data engineering and technology teams to establish trusted, reusable, governed data products and centralized data assets across commercial and corporate investment banking domains
Embed data and AI governance, security, model controls, SOX, auditability, data quality, and regulatory requirements into product design and delivery
Requirements
Bachelor's degree in Computer Science or a closely-related discipline
Join a high-performing team of PhDs, machine vision experts, and algorithm engineers, where you will design and deploy next-generation computer vision and deep learning solutions in complex, high-impact environments.
Compensation
Base Pay Range: $186,200.00 - $316,500.00 Annually
Responsibilities
Design, develop, and optimize advanced machine learning and deep learning algorithms for complex image and signal processing applications
Take ownership of algorithm development from concept and prototyping to production deployment
Invent, evaluate, and implement novel computer vision approaches for challenging, real-world datasets
Analyze system performance, debug complex issues, and improve robustness and accuracy in production environments
Collaborate closely with cross-functional teams (software, systems, applications, and field engineers) to deliver high-quality solutions
This role provides the opportunity to support analytics-enabled initiatives by developing and delivering data analysis and models that address defined business needs post audit closure.
Compensation
Base salary range is expected to be between $94,430.00 CAD - $144,430.00 CAD
Responsibilities
Develop and implement analytics-enabled solutions to improve business processes, generate insights, and support business strategy
Own and deliver end-to-end analytics projects of moderate complexity, while contributing to larger, more complex initiatives
Analyze large and complex datasets to generate actionable insights and translate findings into clear business recommendations
Collaborate closely with business stakeholders and subject matter experts to understand data sources, processes, and business needs
Requirements
Degree in Statistics, Mathematics, Computer Science, Engineering, or a related field
Bachelor’s degree with equivalent technical experience
Lead development and evaluation of oncology foundation models using large-scale omics and clinical datasets within Johnson & Johnson Innovative Medicine.
The anticipated base pay range for this position is: €63,800.00 - €99,820.00
Responsibilities
Collaborate with Oncology Translational Research to develop computational models for precision medicine and drug development
Analyze and integrate high-dimensional biological data, including single-cell and spatial transcriptomics, for model development, training, and validation
Develop and implement scalable statistical, machine learning, and deep learning approaches using large-scale transcriptomic and multimodal datasets
Design rigorous model evaluation strategies, including appropriate benchmarks, validation datasets, and biologically relevant performance metrics
Partner with experimental and translational scientists to design studies that enable robust evaluation and interpretation of computational predictions
Requirements
Ph.D. in computer science, artificial intelligence, bioinformatics, computational biology, statistics, or related quantitative field
Machine Learning Scientist 5 - Bidding & PacingNewNetflix · Remote, US