1 to 25 of 1,475 Remote Algorithms Jobs

business problems. 3. Statistical & Mathematical Modelling and Machine Learning/AI Support the development ofpredictive models, to forecast trends and outcomes Support the development and implementation of machine learning algorithms to address specific business challenges Collaborate with the team to deploy, run, and maintain models in a production environment Evaluate and fine-tune model performance for optimal results. 4. Communication More ❯

business problems. Statistical & Mathematical Modelling and Machine Learning/AI Support the development of predictive models, to forecast trends and outcomes Support the development and implementation of machine learning algorithms to address specific business challenges Collaborate with the team to deploy, run, and maintain models in a production environment Evaluate and fine-tune model performance for optimal results. Communication Create More ❯

of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras). • Proven understanding of software engineering principles, data structures, algorithms, and design patterns. • Experience with version control systems (e.g., Git). • Excellent problem-solving and analytical skills. • Strong communication and collaboration skills. 4. ADDITIONAL DETAILS Please note that candidates may More ❯

client materials and commercial proposals Be the subject matter expert, advising and building solutions, in the contexts of PoC, Datalab or Datalake Have an innovative mindset to implement complex algorithms in a Big Data environment Engineering lead and mentoring; contribute to the development of Data Engineers through knowledge sharing and mentorship Manage the technical relationship between Ekimetrics and our clients More ❯

Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights. Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance. Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings More ❯

Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights. Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance. Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings More ❯

Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights. Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance. Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings More ❯

Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights. Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance. Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings More ❯

Data Analysis and Interpretation: Analyzing large datasets using statistical and machine learning techniques to identify trends, patterns, and insights. Model Building and Evaluation: Developing predictive models using machine learning algorithms to solve business problems. This includes selecting the right algorithms, training models, and evaluating their performance. Data Visualization: Creating clear and impactful visualizations (charts, dashboards, reports) to present data findings More ❯

using Power BI. Familiarity with Microsoft SharePoint, particularly its use in collaborative environments or for data management. Basic understanding of Artificial Intelligence (AI) and Machine Learning (ML) concepts and algorithms . Strong analytical and problem-solving skills with a keen eye for detail. Excellent communication and presentation skills, with the ability to explain complex technical concepts to non-technical audiences. More ❯

and window functions) Good knowledge of Python, including popular Data Science packages (pandas, matplotlib, seaborn, numpy , sklearn ) Familiarity with what is happening under the hood of popular Machine Learning algorithms Strong problem-solving skills and attention to detail Strong communication and collaboration skills Ability to work in a fast-paced, dynamic environment Eagerness to make an impact and lead on More ❯

trends and industry best practices to drive innovation and deliver cutting-edge solutions. Connect to your skills and professional experience Technical Proficiency: Strong understanding of AI concepts, machine learning algorithms, and deep learning architectures. Familiarity with various AI solution design patterns and best practices for different business applications. Experience with data visualization tools and techniques to communicate insights and solution More ❯

D) in various laboratory environments, focusing on mission-critical SIGINT and GEOINT challenges. This role involves leveraging expertise in machine learning, algorithm design, and software development to create tools, algorithms, and prototype capabilities that address emerging intelligence issues. The Software Engineer will work in dynamic lab settings, collaborating with cross-functional teams to design, implement, and optimize innovative solutions under … timelines. The role demands adaptability, technical expertise, and a strong ability to bridge algorithm theory with practical software engineering applications. Key Responsibilities Design, develop, and implement machine learning models, algorithms, and software tools to support SIGINT and GEOINT mission objectives in lab environments. Rapidly prototype and deliver capabilities to address emerging intelligence issues, ensuring alignment with mission requirements. Create and … integrate computer programs, often for larger software systems, to support mission-critical applications. Design and optimize algorithms, conducting analysis, implementation, profiling, and experimental evaluation to ensure performance and scalability. Bridge the gap between algorithm theory and practical applications, translating complex requirements into robust software solutions. Collaborate with lab teams, mission stakeholders, and intelligence analysts to define requirements, prototype solutions, and More ❯

capabilities and affordability checking services Production-Ready Solutions: Transform data science concepts into robust, high-performance code that can handle our production workloads Pragmatic Algorithm Development: Create and optimize algorithms using the most appropriate techniques to solve specific user problems Data-Driven Product Innovation: Collaborate with product teams to translate business requirements into technical solutions that enrich financial data User … of Node.js for backend integration Experience building and deploying data solutions to production environments Practical knowledge of data processing techniques and relevant frameworks Understanding of when to apply ML algorithms vs. simpler approaches to solve problems Experience with statistical analysis and ability to interpret results to drive decision-making Proven ability to clean and prepare data for analysis and enrichment … performance data processing systems Can perform data science analysis independently but focuses on production implementation Understands the difference between exploratory work in notebooks and production-ready code Experience optimizing algorithms for performance and scale Demonstrates a pragmatic approach to problem-solving, always seeking the simplest solution that delivers the best results Can evaluate when machine learning is appropriate and when More ❯

to our company conference and events. What you'll be delivering Collaborate with clients to identify business challenges and opportunities for AI solutions. Design and develop AI models and algorithms to address client needs. Provide technical expertise in AI technologies, including machine learning, natural language processing, and computer vision. Conduct data analysis and preprocessing to prepare datasets for AI model More ❯

predicting novel insights/hypotheses, and other ML techniques. You will collaborate with your team members in applying state of the art ML and graph ML/data science algorithms to this data. You are comfortable working in a team that pushes the boundaries of what is possible with cutting edge ML/AI, challenges the status quo, is laser More ❯

of medical and surgical modalities. Experience in scientific computing and software development with C/C++, Python, or CUDA. Skilled in streaming data processing, performance analysis, and optimization from algorithms to pipelines. Strong time-management and organizational skills for coordinating multiple initiatives, priorities, and implementations of new technology and products into very complex projects. Excellent communication skills particularly in the More ❯

of experience supporting a Financial Operations function •Experience in advanced data analytics, statistical modeling, and predictive analytics using tools such as Alteryx, Python, or R; experience with machine learning algorithms and techniques is a plus. •Experience in building and maintaining APIs for data integration and delivery. •Experience with data warehouse platforms such as Snowflake a plus. ABOUT GOLDMAN SACHS At More ❯

developing and integrating advanced generative AI and ML solutions into existing products and systems, including working with LLMs and agentic workflows. Proficiency in Python and strong knowledge of ML algorithms—ranging from classical techniques to deep learning methods. Proven experience in training, fine-tuning, and deploying neural network models using frameworks like PyTorch, with a focus on optimizing performance and More ❯

This range is provided by Neurolabs. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range Neurolabs is looking for a talented Senior Machine Learning Engineer to join our More ❯

to pursuing their passions. Connecting people across the world is a complex problem with many machine-learning applications. The purpose of this role is to implement mathematical models and algorithms to solve complex business problems in recommendations and classification. Successful outcomes will significantly impact our hundreds of millions of daily active users around the globe. As a Senior Data Scientist … and storytelling skills with both technical and non-technical audiences. Ability to present complex technical subjects to non-technical stakeholders. Ability to read AI research publications and implement the algorithms & architectures from scratch. Advantages Advanced knowledge in generative models: Auto-encoding, adversarial models, compression. Worked on deep learning graph model solutions with 10's of TB of data. Publication in More ❯

who are collectively responsible for creating custom geolocation and digital communications systems in support of national security defense. Core responsibilities include creative problem solving, researching or inventing advanced geolocation algorithms, implementing them in efficient software, testing with real-world data, and deploying to front-line customer facilities. Our dynamic environment and diverse projects demand flexibility to learn new technologies quickly. … The ability to work unsupervised with minimal direction and the ability to self-start is a must. What required background will make you successful? • Expert knowledge of data structures, algorithms, and modern design patterns and data layers • Expert knowledge of Golang • Passion to build internal solutions and own development of enterprise-wide applications • Extensive knowledge of building quality APIs for More ❯

all stages of the data lifecycle Develop and maintain ETL processes for data ingestion and processing Algorithm Development, Model Training and Optimisation Design, develop, and implement advanced machine learning algorithms for fraud prevention and user personalization Train and fine-tune machine learning models using relevant datasets to achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining … to extract meaningful insights and features for model training Code Review and Documentation Conduct code reviews to ensure high-quality, scalable, and maintainable code Create comprehensive documentation for developed algorithms and models Collaboration Collaborate with our cross-functional team; including the founders, sales, data scientists, engineers, and product to understand business requirements and implement effective solutions Research and Innovation Stay … Data Science, or a related field. 7+ years of professional experience in a relevant area like fraud prevention or credit scoring Machine Learning Expertise: Strong understanding of machine learning algorithms and their practical applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and More ❯

all stages of the data lifecycle Develop and maintain ETL processes for data ingestion and processing Algorithm Development, Model Training and Optimisation Design, develop, and implement advanced machine learning algorithms for fraud prevention and user personalization Train and fine-tune machine learning models using relevant datasets to achieve optimal performance Implement strategies for continuous model improvement and optimization Data Mining … to extract meaningful insights and features for model training Code Review and Documentation Conduct code reviews to ensure high-quality, scalable, and maintainable code Create comprehensive documentation for developed algorithms and models Collaboration Collaborate with our cross-functional team; including the founders, sales, data scientists, engineers, and product to understand business requirements and implement effective solutions Research and Innovation Stay … Data Science, or a related field. 7+ years of professional experience in a relevant area like fraud prevention or credit scoring Machine Learning Expertise: Strong understanding of machine learning algorithms and their practical applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and More ❯

exciting period of growth in their London office. In this role, you will join a highly creative, innovative, and passionate team of engineers combining Data Science, AI, ML, optimization algorithms, and automation to enhance human intelligence and solve business problems at scale. You will take on a varied project portfolio, including architecting and implementing robust, modern cloud-based software solutions More ❯