Scientist Analytical Research And Development Jobs

Senior Data Scientist Description - Job Summary • This role is responsible for enabling innovation and creativity by bringing cutting edge perspectives on adopting latest data mining and modelling techniques. The role understands current complex business problems and future business strategy to assess, build and deploy required data mining and modelling capabilities. The role is involved in driving standardization, productivity and cross team learning by establishing processes and SOPs for entire data model development lifecycle. The role drives excellence through continuous improvement in model accuracy and reliability. Responsibilities • Leads organization wide team or teams of other data science professionals in complex projects to mine data using modern tools and programming languages. • Defines models to uncover patterns and predictions creating business value and innovation. • Manages and creates relationships with business partners to evaluate and foster data driven innovation, provides domain-specific expertise in cross-organization projects/initiatives. • Ties insights into effective visualizations communicating business value and innovation potential. • Works with various stakeholders, including business leaders, engineers, product managers, and data analysts, to identify business problems and develop data-driven solutions. • Prepares and presents literature, presentations, invention disclosures for peer review & publication in industry data science domain initiatives and conferences. • Assures insights are communicated regularly and effectively, reviewing designs, models and data compliance. • Defines, communicates and drives data insights/innovation into the business. • Leverages recognized domain expertise, business acumen, and overall data systems leadership to influence decisions of executive business

Abbott is a global healthcare leader that helps people live more fully at all stages of life. Our portfolio of life-changing technologies spans the spectrum of healthcare, with leading businesses and products in diagnostics, medical devices, nutritionals and branded generic medicines. Our 122,000 colleagues serve people in more than 160 countries. JOB DESCRIPTION: Working at Abbott At Abbott, you can do work that matters, grow, and learn, care for yourself and your family, be your true self, and live a full life. You’ll also have access to: Career development with an international company where you can grow the career you dream of. Employees can qualify for free medical coverage in our Health Investment Plan (HIP) PPO medical plan in the next calendar year. An excellent retirement savings plan with a high employer contribution. Tuition reimbursement, the Freedom 2 Save student debt program, and FreeU education benefit - an affordable and convenient path to getting a bachelor’s degree. A company recognized as a great place to work in dozens of countries worldwide and named one of the most admired companies in the world by Fortune.

🚀 About WRITER WRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI. Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI. 📐 About the role AI research at WRITER isn't just about publishing papers — it's about building the scientific foundation that powers some of the most ambitious enterprise AI deployments in the world. As an AI research scientist, you'll be at the center of that work. You'll drive a high-impact research agenda focused on large language models, agentic reasoning, and the system-level capabilities that make AI genuinely useful at enterprise scale. This is a rare opportunity to do research that matters twice over — advancing the field and shipping directly into products used by hundreds of thousands of people every day. We're at an inflection point. Enterprises are moving from experimenting with AI to deeply embedding it across their operations, and WRITER's models are the engine making that possible. The work you do here — on post-training, planning, multi-step reasoning, and agentic workflows — will directly shape how the next generation of enterprise AI behaves, performs, and scales. You

Strength in Trust OneTrust’s mission is to enable innovation through the responsible use of data and AI. We believe that ensuring data is trusted shouldn’t slow teams down—it should accelerate what’s possible. This led us to develop the first technology platform for responsible data use in 2016. Today, with AI representing the latest and most impactful expansion of data yet, OneTrust is once again redefining what responsible innovation looks like. OneTrust, the AI‑Ready Governance Platform™, unifies regulatory intelligence, automation, and connected governance workflows so businesses can continue to move at the speed of AI while ensuring good governance to prevent data misuse at scale. Trusted by thousands of organizations worldwide, OneTrust is shaping the future where trusted data becomes a transformative force for business and society. The Challenge OneTrust's platform supports complex, regulated workflows across privacy, consent, risk, and AI governance. Bringing m easurement maturity to all these areas will help drive a new level of visibility into user experience, ultimately helping our customers achieve their goals. We are hiring a Senior Quantitative UX Researcher to support our teams in data-driven decision-making: to define how experience is measured across the platform, to ensure the underlying data is valid and defensible, and to deliver analysis that informs roadmap decisions. This is the first quantitative research role on a newly expanded UX Research team, responsible for making our numbers defensible and then making them useful. You'll define how we measure the user experience of a complex enterprise platform, build the survey and behavioral measurement that answers real roadmap questions, and partner with designers and mixed methods researchers so that findings arrive with both the scale and the "why." What you'll do Design and run quantitative studies: benchmarking, segmentation, driver analysis, prioritizati

Position Summary Pfizer is seeking a motivated Senior Associate Scientist to join the In Vivo Pharmacology group within the Oncology Research Unit, with a focus on antibody-drug conjugate (ADC) programs, but including other large molecule and small molecule programs. This role supports the execution of in vivo oncology studies that enable ADC discovery and preclinical development, including efficacy, tolerability, pharmacodynamic, and sample collection workflows. The ideal candidate will demonstrate strong technical aptitude, careful attention to detail, and a commitment to animal welfare, compliance, and high-quality study execution. The Senior Associate Scientist is expected to contribute as a dependable technical team member while building scientific understanding of oncology pharmacology and ADC-specific study requirements. Position Responsibilities Execute in vivo oncology studies supporting discovery programs using a variety of in vivo models including human cell line- derived, patient-derived xenograft, syngeneic models as appropriate with minimum guidance from study leads. Perform routine and advanced in vivo procedures, including tumor measurements, body weight monitoring, test article administration (IV, PO, subQ, IP dosing), clinical observations, and sample collection. Perform routine in vitro tissue culture procedures Support pharmacology studies evaluating efficacy, tolerability, pharmacodynamic biomarkers, dosing schedules, and combination approaches. Prepare study materials, confirm dosing and sampling schedules, and ensure study activities are performed according to approved protocols and SOPs. Maintain accurate, timely, and compliant study records using approved electronic data capture and documentation systems. Communicate study observations, technical issues, animal welfare concerns, and timeline risks promptly to managers and study line leads. Collabo

Bloomreach is building the world’s premier agentic platform for personalization .We’re revolutionizing how businesses connect with their customers, building and deploying AI agents to personalize the entire customer journey. We're taking autonomous search mainstream, making product discovery more intuitive and conversational for customers, and more profitable for businesses. We’re making conversational shopping a reality, connecting every shopper with tailored guidance and product expertise — available on demand, at every touchpoint in their journey. We're designing the future of autonomous marketing , taking the work out of workflows, and reclaiming the creative, strategic, and customer-first work marketers were always meant to do. And we're building all of that on the intelligence of a single AI engine — Loomi — so that personalization isn't only autonomous…it's also consistent.From retail to financial services, hospitality to gaming, businesses use Bloomreach to drive higher growth and lasting loyalty. We power personalization for more than 1,400 global brands, including American Eagle, Sonepar, and Pandora. You'd be joining the Artificial Intelligence team . We own the algorithmic core of the platform: Predictions, Contextual Personalization, contextual bandits, autosegmentation, and the agentic workflows behind Loomi. We work with behavioural data at terabyte scale, across 1,400+ customers, in production, every day. We are currently allowing flexibility for our employees to work from anywhere for the respective region (Central & Eastern Europe) or we are happy to meet you in our offices in Bratislava (Slovakia) or Brno, Prague (Czechia) on a full-time basis. The mission You find the signal in how 1,400 brands' customers actually behave — and you prove it moved a business metric. Your models decide which customers are predicted to churn, which segments form themselves, which offer a shopper se

The Opportunity This is an exciting time at Enigma. We’re on the cusp of releasing our next generation of small business intelligence products built on years of learnings in the space. We are seeking an experienced Data Scientist to join our Entity Resolution team and help shape the trajectory of these products. Your work will directly impact the accuracy, scalability, and predictive capabilities of our data platform, influencing key business decisions for our customers. The Role Data is at the core of Enigma’s product, which makes data science the beating heart of what we ship. As a Data Scientist on the Entity Resolution Team, you will work in a cross-functional team alongside other data scientists, engineers, and business stakeholders. You will own problems end to end–from raw source data, through models and scalable pipelines, to the customer interface. Your impact will be measured by the contributions you make with your team to improve the accuracy of our data and the value of our product to our customers. What You’ll Do Translate customer goals into working solutions, using large-scale data transformation, sound statistics, and high-quality code. Most of our work is in Databricks (both Spark SQL + PySpark), supported by statistical tooling, and by ML/AI where the problem calls for it. Set a high standard for rigorous analysis and model development, grounded in sound statistical practice, so that results are high-quality and reproducible. Treat data as a reflection of the real world, and develop repeatable strategies for validating results against ground truth. Develop techniques to detect gaps in our data, find the source, and close them in a way that improves the product. Apply a data-focused, first-principles approach to problem solving. We value people who bias toward simple and elegant solutions, but who can implement state-of-the-art models and techniques when the problem requires it What Makes This Role Exciting? Technical challenge : Enigma

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Location: At Reddit we continue to grow our teams with the best talent. We're completely remote friendly . Team Description: The Marketing Science team at Reddit leverages data to maximize the impact of Reddit’s own marketing investments. We serve as the engine behind our growth, using advanced experimentation, causal inference, and econometrics to understand what drives users to Reddit and what brings advertisers to our platform. We work at the intersection of brand building and performance marketing, ensuring every dollar spent is an investment in the long-term health of our ecosystem. Role Description: Reddit is looking for a highly experienced Staff Data Scientist to lead the strategy and technical execution of our Marketing Intelligence efforts. In this role, you will be the primary architect of how we measure and optimize Reddit’s marketing spend. You will focus on two critical flywheels: B2B Marketing (acquiring and retaining advertisers) and B2C Growth (acquiring and engaging new Redditors). This is a high-autonomy, high-impact role where you will set the long-term strategic goals for Reddit’s marketing measurement, influencing senior leadership and defining how we value our brand and performance efforts. Responsibilities: Set Long-Term Marketing Strategy: Define the 2–3 year technical roadmap for marketing measurement. Establish the "North Star" metrics and frameworks that determine how Reddit allocates hundreds of millions in marketing budget. Optimize Marketing ROI: Build and refine Media Mix Models (MM

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal quality. This is a high-impact, high-autonomy role where you'll influence strategic direction, set a high technical bar, and drive cross-functional initiatives across one or more critical focus areas in the Ads organization. Responsibilities: Design the Future of Ads Identity: Develop/employ probabilistic models for identity resolution. Design the methodology that links on-platform and off-platform actions to maximize addressability while honoring privacy. Advance Lift Methodologies & Experimentation: Own the statistical rigor behind Reddit’s Brand and Conversion Lift products. Innovate experimental design and develop infrastructure that supports large-scale, high-velocity, low-bias testing for advertisers. Maximize Signal for Predictive Performance: Define the strategy for new signal sources. You will mathematically quantify the value of these signals and work with modeling teams to incorporate them into predictive models, directly improving bidding efficiency and ROAS. Define Ground Truth & Evaluation Frameworks: Solve the industry-wide challenge of validating identity and measurement. Design the objective functions and truth sets used to train our models and measure the incremental impact of our identity graph.

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit has a flexible first workforce. At Reddit we continue to grow our teams with the best talent. We're completely remote friendly and will continue to be. Advertising is Reddit’s primary revenue driver and we have an ambitious goal to turn it into a massive business. Although several large digital ad platforms already exist, advertisers are being increasingly drawn to Reddit because of our passionate communities. We believe our community-centric platform has created the opportunity for Reddit to build a highly differentiated ads business. About the Ads Data Science Team: The Ads Data Science team at Reddit leverages data to maximize advertiser value on Reddit through robust data foundations, metrics, and strategic insights generated through experimentation and cutting-edge DS methods. We work on a wide range of challenging problems in the areas of ads and platform measurement, campaign and creative management, advertiser growth and retention, monetization, and the intersection of brand and community engagement. We are a highly collaborative team of passionate data scientists and engineers who are constantly pushing the boundaries of what's possible with machine learning and statistical modeling. About the Role: Reddit’s Ads Data Science team is looking for a highly experienced Staff Data Scientist to advance the intelligence powering the advertiser experience on Reddit. In this role, you'll take deep ownership of a high-impact problem space within advertising, specializing in measurement, identity, and signal

Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com . Reddit is poised to rapidly innovate and grow like no other time in its history. This is a unique opportunity to leave your mark on one of the most influential and trafficked corners of the internet. Consumer data science plays a key role in fulfilling Reddit’s mission of bringing community & belonging to the world through deep understanding of how we can better connect people to the best information and communities for them - the heart of Reddit’s product - from crypto to support groups, gaming to AMAs, travel tips to memes. Reddit's experimentation landscape presents uniquely challenging problems. Our platform is a deeply interconnected network of communities, contributors, and consumers – meaning that standard A/B testing assumptions often break down. We need a senior technical leader who thrives on these hard problems and can raise the bar for causal inference and experimentation rigor across the entire Consumer organization. As a Senior Staff Data Scientist on the Consumer team, you will be the go-to expert on experimentation methodology, owning the most comp

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Develop, test and deploy data pipelines, applications and services Re-shaping, aggregating, enhancing and creating features from datasets Engaging with vendors and internal stakeholders to understand characteristics of datasets Defining and automating qualitative data alerts and reports Partnering closely with investment teams to ensure their data requirements are met Perform preliminary analysis and research to be shared with investment teams REQUIREMENTS Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Attention to detail and a love of processes Strong oral and written communication skills Ability to exercise sound judgment in assessing and determining how to handle queries, calls and issues Ability to multitask and prioritize assignments Commitment to the highest ethica

ROLE We are passionate about data. We collaborate to build elegant, effective, scalable and highly reliable solutions to empower predictive modelling in finance. Cubist’s Data Services (CDS) group is looking for a Data Scientist to join our dedicated data team. Our group is responsible for the timely delivery of comprehensive and error-free data to some of the most demanding and successful systematic Portfolio Managers in the world. As a Senior Data Scientist in the team, this individual will play a vital role in ensuring the smooth day-to-day implementation of a large research infrastructure, and the live production trading of billions of dollars of capital across global capital markets, including equities, futures, options and other financial instruments. RESPONSIBILITIES Onboarding novel datasets from a huge variety of sources into our platform Building processes, tools and frameworks to ingest, clean and deliver datasets Analysis of data for usability, cleanliness, feature extraction and proposed usage by investment teams Creation of in-house, value added, derived data products for consumption by investment teams Engaging with vendors and internal stakeholders to understand characteristics of datasets Partnering closely with investment teams to ensure their data requirements are met Research on new technologies (including AI solutions) to continuously improve data management and value-add for investment teams REQUIREMENTS PhD or Masters in Financial Engineering, Statistics, Computer Science or other disciplines involving rigorous quantitative analysis Strong programming skills in Python and SQL Experience working with AWS, Linux and Airflow preferred but not required 5+ years of experience as a Data Scientist or similar role Experience working with large data sets including predictive modeling Financial industry experience preferred but not required Strong organization, communication and interpersonal skills Intellectua

Scale works with the industry’s leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling). This role will focus on optimizing data curation and eval to enhance LLM capabilities in both text and multimodal modalities. In this role, you will develop novel methods to improve the alignment and generalization of large-scale generative models. You will collaborate with researchers and engineers to define best practices in data-driven AI development. You will also partner with top foundation model labs to provide both technical and strategic input on the development of the next generation of generative AI models. You will: Research and develop novel post-training techniques, including SFT, RLHF, and reward modeling, to enhance LLM core capabilities in both text and multimodal modalities. Design and experiment new approaches to preference optimization. Analyze model behavior, identify weaknesses, and propose solutions for bias mitigation and model robustness. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning. Excellent written and verbal communication skills Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals Previous experience in a customer facing role. Compensation packages at Scale for eligible roles include base salary, equity, and benefits. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position and may be inclusive of several career levels at Scale; it will be determined du

Scale works with the industry's leading AI labs to provide high quality data and accelerate progress in GenAI research. We are looking for Research Scientists and Research Engineers with expertise in LLM post-training (SFT, RLHF, reward modeling) and evaluation. This role is on the evaluation pod within the GenAI Research Organization and will focus on building benchmarks and diagnosing model failure modes in both text and multimodal modalities. In this role, you will develop rigorous evaluations and diagnostic methods that reveal where frontier models fail and why. You will collaborate with researchers and engineers to define best practices in evaluation-driven AI development. You will also partner with top foundation model labs to translate failure analysis into technical and strategic input on the next generation of generative AI models. You will: Analyze model behavior to identify, characterize, and diagnose failure modes in frontier LLMs and Agents. You’ll identify everything from capability gaps and reasoning errors to robustness and alignment issues, all focusing on RCA. Design and build benchmarks and evaluation methods that measure LLM capabilities in both text and multimodal modalities. Apply post-training expertise (SFT, RLHF, reward modeling) to connect observed failures to the data and training interventions that address them. Publish research findings in top-tier AI conferences. Ideally you’d have: Ph.D. or Master's degree in Computer Science, Machine Learning, AI, or a related field. Deep understanding of deep learning, reinforcement learning, and large-scale model fine-tuning. Experience with post-training techniques such as RLHF, preference modeling, or instruction tuning, and with LLM evaluation or benchmark development. Excellent written and verbal communication skills. Published research in areas of machine learning at major conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, CVPR, etc.) and/or journals. Previous experience in a customer facing r