Scientist 1 Jobs

🚀 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

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential. Title and Summary Senior Data Scientist-2 Overview Product Data & Analytics is a centralized global team that enables Mastercard product business units to make better data‑driven decisions. We build internal analytics partnerships that strengthen focus on business performance, portfolio and revenue optimization, initiative tracking, new product development, and go‑to‑market strategies. These capabilities are underpinned by our data platforms that enable insights to be delivered in a standardized, scalable, and cost‑efficient manner. Key Responsibilities Strategic Support • Design and implement value enablement frameworks that optimize pricing strategies, enhance pre-sales propositions, and ensure customer success. • Collaborate with global and regional teams to tailor solutions that meet regional business needs and align with Mastercard's objectives. • Provide data-driven insights and recommendations to optimize pricing, pre-sales strategies, and customer success outcomes. • Develop frameworks, project structures, and presentations to communicate key strategic initiatives. • Conduct data integrity checks and ensure quality and reliability in data used for analysis. • Translate complex business problems into analytical solutions that support strategic decision-making. Technical Leadersh

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

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

MeltPlan | Planning Engine for the Built Environment MeltPlan is building the “planning engine” for the $14 Tn construction industry, an AI system designed specifically to optimize decisions before construction begins. While design software optimizes use and aesthetics and construction software optimizes execution and control, MeltPlan is building the missing layer - software that optimizes decisions and tradeoffs upstream, before scope is locked, procurement begins, and change orders become inevitable. MeltPlan’s long-term goal is to help teams make construction “boring” by making planning more intense: surfacing constraints and tradeoffs early, aligning stakeholders before plans are frozen, and reducing the need for late-stage redlines, rework, and change orders. MeltPlan is founded by operators who have built at scale. Kanav previously co-founded Innovaccer, a $3Bn healthtech company focused on making US healthcare more affordable and accessible. He’s now applying that systems-level thinking to construction.He’s joined by Tanmaya Kala, former Project Executive at DPR Construction, who led large commercial, healthcare, and life sciences projects. We combine deep tech scale with real construction execution. What This Role Really Is We are looking for an AI Research Scientist – Computer Vision to enhance and manage the PlanGraph model, which transforms 2D drawings into structured graphical representations of building elements. The role involves solving downstream business use cases such as quantity takeoff, code compliance, value engineering, and constructability analysis.We are specifically looking for hands-on researchers with experience in solving real-world Computer Vision problems and building custom vision models, VLMs, or VLLMs for production-grade applications. What You’ll Do Build and optimize custom Computer Vision models, VLMs, and VLLMs for construction intelligence workflows. Solve downstream business use cases including quantity takeoff, code complianc

About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary Reporting to the Quality leadership within Manufacturing Operations, the Senior Reliability Scientist is responsible for leading reliability activities across complex, high-performance systems. Working closely with established reliability experts and cross-functional teams, this role uses experimental data and advanced modelling to inform design decisions, validate product reliability and optimise serviceability strategies, including spares provisioning. The Team The Quality team within Manufacturing Operations is responsible for ensuring product robustness, reliability and lifecycle performance across Graphcore’s hardware portfolio. The team includes experienced reliability specialists and works closely with technology research, chip, board, system design, platform and operations teams to translate reliability insights into actionable improvements across the product lifecycle. Responsibilities and Duties: · Define and refine reliability requirements across silicon, board and system levels, working in partnership with research and design teams · Apply ad

Opportunity Overview: As a Staff Data Scientist at Cohere Health, you will serve as a technical leader across high-priority initiatives, shaping how data science is applied to some of the most complex challenges in healthcare. You’ll drive the design of advanced analytical and modeling solutions, influence strategic direction, and partner deeply across Product, Clinical, and Engineering to deliver scalable, high-impact outcomes. This role goes beyond execution. You’ll define approaches, set standards, and guide others in solving ambiguous, high-leverage problems. You’ll play a critical role in advancing the maturity of data science at Cohere while contributing directly to improving clinical and operational decision-making. What you’ll do: Lead the design and execution of complex, high-impact data science initiatives across multiple domains Define analytical frameworks and modeling approaches for ambiguous, strategic problem spaces Partner with senior stakeholders to shape problem definition, prioritize opportunities, and influence decision-making Develop and deploy advanced models and scalable analytical solutions that drive measurable outcomes Establish best practices for experimentation, model development, and analytical rigor across the team Mentor and guide other data scientists, providing technical leadership and elevating team capabilities Drive cross-functional alignment to ensure solutions are practical, scalable, and integrated into workflows ISMS roles and responsibilities: Good knowledge of Information security Oversee specific business processes within the ISMS. Responsible to manage the ISMS documentation, conduct risk assessments, and implement risk treatment plans. Risk Owners are responsible for identifying, assessing, and managing risks within their areas of responsibility. They are also responsible for implementing risk treatment plans. Conduct the BCP and other test related to information security continuity along with CISO Responsible for monitor

At FourKites we have the opportunity to tackle complex challenges with real-world impacts. Whether it's medical supplies from Cardinal Health or groceries for Walmart, the FourKites platform helps customers operate global supply chains that are efficient, agile and sustainable. Join a team of curious problem solvers that celebrates differences, leads with empathy and values inclusivity. As a Senior Data Scientist, you will build and own machine learning models that power core prediction problems across the FourKites platform — including ETA/ATA forecasting and message-based status extraction. You will work end-to-end, from data pipeline to production deployment and monitoring, turning noisy real-world logistics data into models that run at scale and directly move the needle on customer outcomes. You will work closely with product, engineering, and operations teams, hands-on building and shipping models yourself while also guiding the technical direction of other data scientists on the team. What you'll be doing: Design, build, and productionize ML models for problems like ETA/ATA prediction, using regression, classification, and time-series forecasting techniques Develop NLP/LLM-based extraction pipelines for message-based ETA and status updates (text extraction, entity recognition) Own models end-to-end: data pipeline → training → deployment → monitoring → retraining Work with noisy, real-world logistics and supply chain data (GPS pings, check calls, carrier data) rather than clean, pre-processed datasets Diagnose gaps between offline evaluation performance and live production accuracy, and drive fixes Build and maintain automated training/retraining pipelines using orchestration tools such as Airflow Set up and maintain model monitoring and observability (e.g., Grafana) to catch drift and degradation proactively Replace manual or rule-based processes with ML-driven automation (e.g., automating manual check calls) Translate model performance improvements into busin

ROLE SUMMARY We are looking for a Senior Data Scientist to lead complex data science engagements that combine traditional statistical modelling with Generative AI. You will work hands-on with very large datasets across disparate systems and formats, translate ambiguous business problems into rigorous analytical solutions, and present those solutions clearly to C-level stakeholders. This is a delivery-first role with a fast track into technical leadership: alongside your own project work, you will help guide junior data scientists and shape how Lynx builds and ships data science solutions. KEY RESPONSIBILITIES Solution Design & Delivery Design and deliver end-to-end solutions for defined data science problems, combining classical modelling, data transformation, and Generative AI / LLM techniques. Work hands-on with very large datasets across disparate stores and formats, from ingestion and transformation through to modelling and validation. Apply statistical and machine learning methods to business problems such as customer retention, campaign management, and commercial performance optimisation. Client Communication & Leadership Present results and prepare client-ready materials for project stakeholders, including C-level audiences, translating technical work into clear business narratives. Lead smaller data science workstreams, with support from internal leadership and the PMO, including day-to-day guidance for junior team members. Partner with delivery and account teams to scope problems, set realistic timelines, and manage stakeholder expectations. Knowledge Building Create reusable documentation, presentations, and code libraries during projects so future engagements can build on prior work. Participate in internal education, research, and knowledge-sharing initiatives that raise the technical bar across the practice. SKILLS, QUALIFICATIONS AND EXPERIENCE 8+ years of overall experience in data science, with a track record of leading analytic

Sigmoid Analytics is a leading Data solutions company backed by Sequoia Capital. We offer best in- end-to-end data value chain spanning across Data Science, Data Engineering and Data Ops. With data and technology at the core of our solutions, we are solving some of the toughest problems out there. Our culture is modelled around expertise and mutual respect with a team first mindset. You’ll work with teams that push the boundaries of what-is-possible and build solutions that energize and inspire. Offices : New York | Dallas | San Francisco | Lima | Bengaluru The below role is for our Bengaluru office. About the Role : You will work on a broad range of cutting-edge data science and machine learning problems across a variety of industries. You will be engaging with clients to understand their business context. If you are passionate to work on complex unstructured business problems that can be solved using data science and machine learning we would like to talk to you. Function : Data Science and Analysis → Data Science / Machine Learning Desired Skills & Competencies: Strong learning acumen Team Management High sense of ownership Ability to work in a fast-paced and deadline-driven environment Loves technology Highly skilled at Data Interpretation Problem solver Good exposure to machine learning concepts and algorithms Must be fluent with any one of Python, R, Java Strong in statistical & machine learning concepts Knowledge of Python Libraries - SciPy, NumPy, Pandas, I Python, Scikit-learn Knowledge of distributed big data processing (PySpark, Jupyter, Linux, AWS) Responsibilities: Hypothesis testing, insights generation, root cause analysis, factor analysis Statistical model (predictive & prescriptive) development using various statistical & machine learning techniques/algorithms Test/train the model, Improve Model accuracy, Monitor model performance Data Extraction from EDW/Big Data Platform, Dataset Preparation (creation of base data, aggregation