Remote Jobs in Europe

Data science

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🔥 Senior Machine Learning Engineer

Posted about 2 hours ago

📍 Brazil, the U.S., and Canada

🧭 Full-Time

🔍 Payments

🔧 Requirements

Bachelor’s or Master’s degree in CS/Engineering/Data-Science or other technical disciplines.
Solid experience in DS/ML engineering.
Proficiency in programming languages such as Python, Scala, or Java.
Hands-on experience in implementing batch and real-time streaming pipelines, using SQL and NoSQL database solutions
Familiarity with monitoring tools for data pipelines, streaming systems, and model performance.
Experience in AWS cloud services (Sagemaker, EC2, EMR, ECS/EKS, RDS, etc.).
Experience with CI/CD pipelines, infrastructure-as-code tools (e.g., Terraform, CloudFormation), and MLOps platforms like MLflow.
Experience with Machine Learning modeling, notably tree-based and boosting models supervised learning for imbalanced target scenarios.
Experience with Online Inference, APIs, and services that respond under tight time constraints.
Proficiency in English.

💡 Responsibilities

Design the data-architecture flow for the efficient implementation of real-time model endpoints and/or batch solutions.
Engineer domain-specific features that can enhance model performance and robustness.
Build pipelines to deploy machine learning models in production with a focus on scalability and efficiency, and participate in and enforce the release management process for models and rules.
Implement systems to monitor model performance, endpoints/feature health, and other business metrics; Create model-retraining pipelines to boost performance, based on monitoring metrics; Model recalibration.
Design and implement scalable architectures to support real-time/batch solutions; Optimize algorithms and workflows for latency, throughput, and resource efficiency; Ensure systems adhere to company standards for reliability and security.
Conduct research and prototypes to explore novel approaches in ML engineering for addressing emerging risk/fraud patterns.
Partner with fraud analysts, risk managers, and product teams to translate business requirements into ML solutions.

AWS Backend Development Docker Python SQL Amazon RDS AWS EKS Frontend Development Java Kafka Kubernetes Machine Learning MLFlow Airflow Algorithms Data engineering Data science REST API Nosql Pandas Spark CI/CD Terraform Scala Data modeling English communication

Posted about 2 hours ago

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🔥 Principal Machine Learning Scientist (UK Remote)

Posted about 2 hours ago

📍 United Kingdom

🧭 Full-Time

🔍 Education

🔧 Requirements

Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus.
A strong understanding of the math and theory behind machine learning and deep learning.
Software engineering background with at least 3-5 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).
An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.
Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.
Excellent communication and teamwork skills.
Fluent in written and spoken English.

💡 Responsibilities

Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered.
Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices.
Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs.
Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings.
Optimize models for scaled production usage.
Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners.
Write clean, efficient, and modular code, with automated tests and appropriate documentation.
Stay up to date with technology, make good technological choices, and be able to explain them to the organization.

AWS Docker Python Software Development SQL Bash Data Analysis Frontend Development Git Machine Learning Numpy PyTorch Algorithms API testing Data science Data Structures REST API CI/CD RESTful APIs JSON Data visualization

Posted about 2 hours ago

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🔥 Director, Data Science (REMOTE: US)

Posted about 3 hours ago

📍 United States

💸 228100.0 - 325800.0 USD per year

🔍 Software Development

🏢 Company: Veeam Software👥 5001-10000💰 $2,000,000,000 Secondary Market 4 months ago🫂 Last layoff about 1 year agoVirtualization Data Management Data Center Enterprise Software Software Cloud Infrastructure

🔧 Requirements

Extensive experience in Data Analytics, Business Intelligence, and Reporting, with a strong focus on statistical methods
Advanced expertise in AI and Machine Learning, including model development, deployment, and designing AI-driven solutions for business processes
Proficient in technologies like Python, R, and TensorFlow, with formal training in Data Science and hands-on experience in machine learning libraries and data visualization techniques
Expertise in SQL queries, Excel, PowerPoint, and SaaS systems like Salesforce
Strong analytical skills and experience in AI-driven solutions
Experience with cloud computing platforms such as AWS, Azure, and Google Cloud
Proven ability to lead AI projects and implement innovative technologies that drive business value
Strong problem-solving skills and ability to handle complex datasets to extract actionable insights
Effective communication skills to articulate complex analytical concepts to technical and non-technical stakeholders

💡 Responsibilities

Lead and mentor a team of data scientists in developing advanced machine learning models, dashboards, and visualizations for predictive analytics and decision-making
Conduct and supervise statistical analyses and experiment-driven predictive modeling to extract actionable business insights, leveraging cutting-edge machine learning algorithms
Present analytical findings and recommendations to stakeholders and leadership, utilizing AI for enhanced data interpretation and driving strategic decisions
Identify and leverage data opportunities with cross-functional teams through AI-powered data mining techniques and unstructured problem-solving
Lead the deployment of secure, scalable data science solutions using Python, R, SQL, and AI frameworks to address complex business challenges
Implement and monitor automated anomaly detection systems using machine learning to swiftly identify and address issues
Design comprehensive experiments to validate models, ensuring robust and reliable outcomes
Drive innovation by continuously exploring and integrating new AI technologies and methodologies
Optimize operational workflows using AI and machine learning techniques, enhancing efficiency and productivity
Develop and refine complex algorithms to solve unstructured problems, applying deep learning and other advanced techniques
Ensure robust data quality and integrity with AI-driven cleaning and validation procedures
Communicate complex analytical concepts in a clear and concise manner to stakeholders, fostering understanding and collaboration across teams

AWS Python SQL Cloud Computing Data Analysis Data Mining Machine Learning Numpy Cross-functional Team Leadership Algorithms Data science Pandas Tensorflow Data visualization Data modeling Data analytics SaaS PowerPoint

Posted about 3 hours ago

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🔥 Data Scientist

Posted about 5 hours ago

📍 South Africa

🔍 Finance & Technology

🏢 Company: JUMO👥 251-500💰 $120,000,000 over 3 years agoMobile Payments Big Data Financial Services Banking InsurTech FinTech

🔧 Requirements

A bachelor's degree with a strong quantitative component (e.g. Economics, Physics, Engineering, Software engineering, etc.).
Minimum 3-5 years of experience filling a similar role in Finance & Technology.
Strong data wrangling skills using SQL and coding in python.
Strong interest in software development.
An ability to interpret problems, and simplify them to their essentials.
The desire to innovate, be creative and work on challenging problems.
Experience using software development practices like git, CI/CD, etc.

💡 Responsibilities

Analyse, transform, augment and build datasets to convert financial and behavioural data into features and dimensions that allow us to more easily and accurately extract insights.
Use your coding skills to contribute to our team tooling and automate processes as much as possible.
Design and develop models of our real world systems and client behaviours to help inform our decision making. This includes, but is not limited to, forecasting, simulating products or systems, testing decline strategies, and optimising client experience.
Analyse end user requirements to understand and communicate what our stakeholders (for example, fellow analysts, portfolio managers, or partners) need, and what we can deliver to match those expectations.
Derive and communicate insights to our stakeholders.

AWS Python SQL Cloud Computing Data Analysis Git Machine Learning Algorithms Data science Analytical Skills CI/CD Problem Solving RESTful APIs Data visualization Financial analysis Data modeling Finance

Posted about 5 hours ago

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🔥 Data Scientist

Posted about 7 hours ago

📍 South Africa

🔍 Finance & Technology

🏢 Company: Employee Referrals

🔧 Requirements

A bachelor's degree with a strong quantitative component (e.g. Economics, Physics, Engineering, Software engineering, etc.).
Minimum 3-5 years of experience filling a similar role in Finance & Technology.
Strong data wrangling skills using SQL and coding in python.
Strong interest in software development.
An ability to interpret problems, and simplify them to their essentials.
The desire to innovate, be creative and work on challenging problems.
Experience using software development practices like git, CI/CD, etc.

💡 Responsibilities

Analyse, transform, augment and build datasets to convert financial and behavioural data into features and dimensions that allow us to more easily and accurately extract insights.
Use your coding skills to contribute to our team tooling and automate processes as much as possible.
Design and develop models of our real world systems and client behaviours to help inform our decision making. This includes, but is not limited to, forecasting, simulating products or systems, testing decline strategies, and optimising client experience.
Analyse end user requirements to understand and communicate what our stakeholders (for example, fellow analysts, portfolio managers, or partners) need, and what we can deliver to match those expectations.
Derive and communicate insights to our stakeholders.

Python SQL Data Analysis Git Machine Learning Data engineering Data science REST API Analytical Skills CI/CD Data visualization Financial analysis Data modeling

Posted about 7 hours ago

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🔥 Head of Product - Identity Resolution & Deliverability

Posted about 7 hours ago

📍 United States

🧭 Full-Time

🔍 Adtech or martech

🏢 Company: Elvis Eckardt Recruitment & Sales Solutions Limited

🔧 Requirements

7+ years in Product Management in adtech or martech, with 3+ years in a leadership role.
Demonstrated ability to define and execute a strategic roadmap.
Experience in identity resolution, audience segmentation, or email deliverability.
Strong command of product analytics, feedback loops, and user adoption.
Proven cross-functional leadership with Engineering, Marketing, Sales, and CX.

💡 Responsibilities

Codify product strategy in partnership with CTO, COO, and CEO.
Lead enhancements of graph accuracy, data coverage, and clustering methods.
Gather, analyze, and act on qualitative and quantitative customer feedback.
Maximize client inbox placement rates, and reduce spam complaints.
Align engineering, sales, marketing, and customer success on delivery plans.
Partner with Legal to ensure all roadmap items remain compliant with evolving regulations.

SQL Data Analysis GCP Kafka Product Management Salesforce Cross-functional Team Leadership Product Development Strategy Product Analytics Data science Agile methodologies RESTful APIs Customer Success

Posted about 7 hours ago

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🔥 Director, AI Solution Partners - Operations

Posted about 8 hours ago

📍 United States

💸 190605.0 - 226526.0 USD per year

🔍 Biotech

🏢 Company: careers

🔧 Requirements

Advanced degree (e.g., Master’s or PhD) in AI, Machine Learning, Data Science, or related field.
10+ years of leadership roles within pharmaceutical, biotech, or healthcare industries.
Deep domain expertise in biopharma Operations including direct experience working within the biopharma Operations domain
At least 3 years of AI experience within the biopharma Operations domain
Demonstrated ability to lead multi-functional teams and manage complex initiatives in a matrixed organization.
Hands-on experience with AI/ML tools, technologies, and platforms, as well as a solid understanding of data ecosystems.
Demonstrable ability to prioritize and manage a portfolio of initiatives aligned with business strategy.
Experience partnering with external technology providers and managing alliances to deliver enterprise-scale AI solutions.
Familiarity with regulatory requirements and data privacy considerations in the pharmaceutical or biotech sector.
Strong track record of developing and driving AI strategies that align with organizational goals across functional areas.
Experience influencing senior leadership and advocating for AI initiatives with non-technical stakeholders.

💡 Responsibilities

Partnering with business leaders to guide prioritization and investment decisions
Partner with broader AI&D and Lab teams (Alliances and Ecosystem, Digital Product Management, Lab Accelerator) to implement and validate AI solutions that solve critical challenges.
Fostering cross-functional collaboration across AI&D, Tech, and business units
Ensure successful delivery and adoption of AI solutions within the assigned function, driving measurable outcomes and enterprise scalability.

AWS Leadership Project Management Python Artificial Intelligence Machine Learning Cross-functional Team Leadership Operations Management Strategy Business Operations Data science Communication Skills Analytical Skills Collaboration RESTful APIs Problem-solving skills Data visualization Stakeholder management Strategic thinking Data modeling Data analytics Data management Change Management

Posted about 8 hours ago

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🔥 2025 - Digital Pathology Intern

Posted about 9 hours ago

📍 Canada

🧭 Internship

🔍 Software Development

🏢 Company: roche-ext

🔧 Requirements

Must be enrolled in a MSc/PhD program in Biomedical Engineering, Statistics, Mathematics, Data Science, Electrical Engineering, Computer Science or related field; PhD candidate preferred.
In-depth knowledge of machine learning and deep learning, with a focus on imaging data, especially biomedical imaging.
Experience with omic data analysis, large language model (LLM), multimodal analysis or Generative Adversarial Network (GAN) is advantageous.
Proficiency in parallelization, HPC cluster computing, Python, deep learning frameworks, and reproducible research practices (like Git).
Strong communication and collaboration skills, coupled with a passion for applying machine learning to healthcare.
Preferred experience includes publications in top conferences/journals and contributions to open source projects.

💡 Responsibilities

Collaborate with the team and other stakeholders to evaluate state-of-the-art computer vision techniques and applications in pathology image analysis, particularly with deep-learning and machine-learning approaches
Devise, implement and interpret deep learning algorithms to address selected research questions in digital pathology
Proactively share findings and knowledge to support the development of the wider Roche community
Help shape the direction of machine learning and artificial intelligence within Roche.

Python Git Image Processing Machine Learning Algorithms Data science

Posted about 9 hours ago

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🔥 Senior Data Scientist

Posted about 12 hours ago

📍 United States

🧭 Full-Time

🔍 Real Estate

🏢 Company: Property Leads👥 11-50 Real Estate

🔧 Requirements

4+ years of experience working with real estate data, particularly niche data sets (divorce, bankruptcy, probate, etc.).
Proficiency in data analysis and engineering tools (e.g., SQL, Python, Pandas, Excel).
Experience with data platforms and lead generation tools (e.g., PropStream, BatchLeads).
Experience developing scoring models, predictive features, or data-driven segmentation.
Strong understanding of ETL pipelines, public record APIs, and/or scraping strategies
Proven ability to source and curate high-quality leads.
Meticulous attention to detail and a passion for clean, actionable data
Excellent communication skills and a collaborative, fast-moving mindset.

💡 Responsibilities

Source and analyze specialized real estate data sets, including: Divorce records Bankruptcy filings Probate cases Tax liens, pre-foreclosures, and other distressed property indicators
Develop and maintain efficient processes for extracting, cleansing, and managing data from multiple sources.
Identify patterns and insights in data to improve lead targeting and conversion rates.
Collaborate with the marketing and sales teams to create actionable lead lists and improve outreach strategies.
Stay current with trends and tools in real estate data sourcing and analysis.
Ensure data accuracy, completeness, and compliance with relevant regulations.
Provide input into data roadmap, tooling decisions, and long-term analytics strategy
Mentor junior analysts or data contributors (as team grows)

Python SQL Data Analysis Data Mining ETL Machine Learning Data science Pandas RESTful APIs Data visualization Lead Generation Data modeling

Posted about 12 hours ago

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🔥 Principal Machine Learning Scientist (UK Remote)

Posted about 14 hours ago

📍 United Kingdom

🧭 Full-Time

🔍 Education

🔧 Requirements

Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised.
A strong understanding of the math and theory behind machine learning and deep learning.
Software engineering background with at least 3-5 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review).
Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases).
An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families.
Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. A Computer Science background is required as opposed to statistics or pure mathematics. We’re an applied science group leaning towards deep learning and therefore software development proficiency is a prerequisite.
Excellent communication and teamwork skills.
Fluent in written and spoken English.

💡 Responsibilities

Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered.
Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices.
Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary.
Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters.
Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs.
Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings.
Optimize models for scaled production usage.
Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners.
Write clean, efficient, and modular code, with automated tests and appropriate documentation.
Stay up to date with technology, make good technological choices, and be able to explain them to the organization.

AWS Docker Python Software Development SQL Data Analysis Frontend Development Git Machine Learning Numpy PyTorch Algorithms Data science Data Structures Communication Skills Analytical Skills CI/CD Problem Solving Software Engineering

Posted about 14 hours ago

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