626 to 650 of 5,455 Computer Science Jobs

algorithms that uncover patterns of life, and deliver intuitive visualizations that accelerate sense-making and operational advantage. Work with us as we apply data science to advance national security missions. The Opportunity: E nga ge stakeholders to elicit analytic questions and transform them into technical requirements and prioritized backlogs … evolution of analytic tradecraft leveraging modern data ecosystems. Join us. The world can’t wait. You Have: 5+ years of experience in data science, including exploration, cleaning, analysis, visualization, or data mining, with demonstrated work across structured and unstructured sources Experience in Python and SQL or R, and with ...

This role focuses on designing and delivering AI, data science, and advanced analytics solutions using the Microsoft Azure technology stack. You will work on projects spanning AI, machine learning, and data platforms for customers, taking responsibility from problem definition through to production delivery. Alongside hands‐on technical work … comfortable speaking with clients and some occasional travel. RESPONSIBILITIES Delivering projects that utilise the Microsoft Azure technology stack across domains such as AI, Data Science & Machine Learning & advanced analytics Contributing to the creation of new AI- and data science-based offerings based on maintaining an awareness of ongoing ...

Compliance is all about challenging the status quo and striving to be best in class. As a Vice President, Data Scientist in the Data Science team, you will help us shape the future of financial services by developing and implementing advanced AI solutions. You will collaborate with product, engineering … business value. In this role, you will have the opportunity to experiment, learn, and innovate alongside a diverse team, leveraging your expertise in data science and finance. Together, we will deliver solutions that transform how we operate and serve our clients. Join us to make a meaningful difference ...

Engineering Lead 15 To represent the company in a professional manner at all times Person Specification Essential Desirable Qualifications Master’s or PhD in Computer Science, Artificial Intelligence, or related field. Related research publications. Experience Experience in machine learning engineering or applied AI. Recent demonstrable experience with LLMs … e.g., RAGAS, TruLens) for testing LLM outputs. Deep expertise in GCP Vertex AI (preferred) or equivalent cloud platforms.. Background in mathematics, statistics, or theoretical computer science Deep expertise in GCP Vertex AI (preferred) or equivalent cloud platforms.. Deep understanding of APIs, containerization (Docker), and CI/CD pipelines. ...

technical audiences Ensure adherence to all applicable risk, control, and governance requirements Required Qualifications, Capabilities, and Skills: Bachelor's degree in AI, Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative discipline Experience developing and deploying machine learning or AI solutions using modern tools … large language models, agentic frameworks, or generative AI technologies Experience with statistical analysis, experimentation, and model evaluation methodologies Proficiency in Python, SQL, and data science tooling used in enterprise environments Strong analytical, problem-solving, and communication skills Ability to manage multiple priorities and deliver results in a collaborative environment ...

efficiency of infrastructure. Maintain software repositories and apply software updates. Maintain documentation for procedures, configurations, and programs. Required Skills & Qualifications: Bachelor's degree in computer science, engineering, or equivalent experience. 5+ years of experience working with Linux operating systems in production. Strong scripting skills in Python, Ruby, Perl … documentation skills. Preferred Skills: Experience with cloud computing. Experience with open-source application suites such as WordPress or Drupal. Master's degree in computer science, information technology, or a related field. Work Arrangement & Interview Process Hybrid schedule with a minimum of 3 days onsite per week. Onsite ...

Ensure responsible AI deployment, embedding ethical and regulatory considerations into every stage of development. Skills, Knowledge & Expertise Bachelor’s or Master’s degree in Computer Science, Machine Learning, or a related technical field – or equivalent practical experience. 3+ years of professional experience as an ML Engineer, or related … internal services, e.g. via FastAPI; Deploying containerised systems to production, in particular via Kubernetes. In addition, the following would be an advantage: PhD in Computer Science, Machine Learning, or a related field with a strong publication record in text analytics, representation learning, or applied predictive modelling. Practical experience ...

design, build, test, and deploy scalable AI services integrated with strategic systems and operational processes. You will collaborate with software engineers, AI and data science specialists, operations stakeholders, and business partners to improve operational workflows, controls, and the software development lifecycle. You will focus on hands-on engineering across … software engineering use cases Build and enhance robust, scalable, reusable AI services and supporting infrastructure using modern technologies Collaborate with AI and data science specialists to design, develop, test, and deploy services integrated with strategic systems and operational processes Learn Markets Operations processes and apply that knowledge to develop ...

date on the latest advancements in AI and machine learning.* Utilize combined knowledge of data structures, analytics, algorithms/models, and strong computer science fundamentals to independently prepare datasets, conduct analytics, and develop deployable solutions* Collect, analyze and interpret large data assets to define and build multiple innovative … data scientists, guiding them on deliverable quality and accuracy**What experience you need*** Bachelor's degree (2:1 or above) in a numerical subject (Computer Science, Mathematics, Statistics, Physics, Engineering).* Solid experience in data analysis, machine learning, and AI development.* Hands-on experience with cloud-based ...

digital transformation service providers, we are expanding our Data and AI Practice across Europe to meet growing client demand for advanced AI and data science solutions. The ideal candidate will have a deep understanding of artificial intelligence, machine learning and analytics, combined with IT consulting experience and domain expertise … demos, and RFP responses Stay current on industry trends, regulatory updates, and emerging AI technologies Requirements Bachelor's or Master's degree in Data Science, Computer Science, Finance, Economics, or related field (Ph.D. a plus) 5+ years in data science or AI roles within financial services ...

initial supervision with external clients at appropriate levels. Knowledge, Skills, Experience & Qualifications University degree in finance/economics/business, mathematics/econometrics/computer science or related subject from a leading university in the country of education. Quantitative/numerical skills are essential with the ability … interpret financial information and understand financial accounts and reports. Solid understanding of how financial accounts relate to one another. Computer literacy, conversant with Microsoft Office 365 applications, Excel (VBA is a plus). Knowledge of data, databases and statistical systems a plus; Knowledge of SQL with the ability ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion cleaning EDA modeling validation deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion cleaning EDA modeling validation deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion cleaning EDA modeling validation deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion cleaning EDA modeling validation deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects. Although every project is unique, you might typically: Design original computational data science … real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency. Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations). Incorporate big data processing scenarios requiring scalable computational approaches. Verify solutions using Python with standard ...

work on meaningful challenges with direct impact on national infrastructure. You'll collaborate with engineers, operators and technology teams while applying cutting-edge data science and machine learning techniques in a production environment. What you'll be doing Develop forecasting, optimisation and machine learning models to solve operational … asset management challenges. Take ownership of data science projects from discovery through to production deployment. Analyse and prepare large datasets from operational, asset, weather and market sources. Build and maintain MLOps pipelines to support reliable and scalable model deployment. Create dashboards, visualisations and applications that communicate insights to stakeholders. ...

class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering … class operations and investments in research and development, we offer capabilities and opportunity no one else can. Together, we push the boundaries of known science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering ...

driven architecture, and Domain-Driven Design (DDD). Experience in asynchronous and parallel processing. Scalable distributed system design. Technical Skills & Tooling: Strong foundation in computer science concepts including data structures, algorithms, and OOP. Experience in relational data modeling, schema design, and SQL using Oracle or SQL Server. DevOps … Proven experience in large-scale enterprise ECM implementations. Proven experience in managed services, support, and transformation engagements. Bachelor's or Master's degree in Computer Science, IT, or a related field. Benefits: Our Benefits Include: Medical, Dental, and Vision Insurance 401(k) Retirement Plan Health Savings Account ...

validate, and monitor data quality. - Perform feature engineering and exploratory data analysis. - Develop data quality metrics and visualizations to identify trends and opportunities. Data Science, Machine Learning & Advanced Analytics - Design, develop, deploy, and monitor statistical and machine learning models. - Select appropriate statistical methods, modeling techniques, and algorithms. - Design … agentic AI, and large language models (LLMs), where appropriate to enhance analytical solutions. Technical Leadership & Solution Delivery - Lead multiple medium- to large-scale data science initiatives from concept through implementation. - Translate business challenges into analytical solutions. - Define technical approaches and project methodologies. - Establish best practices for data science ...

Branding allows us to identify opportunities, solve complex problems, and build robust data solutions. This is an exciting opportunity to apply cutting-edge data science techniques in a fast-paced, high-volume, and globally recognised industry, utilising a modern and powerful tech stack. This role is eligible for inclusion … Companys hybrid work from home policy. Qualifications Excellent analytical, problem-solving, and critical thinking skills. PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field. Experience using core machine learning techniques, such as regressions, classification,clusteringand deep learning. Strong programming skills in languages such as Python ...