Remote Data Science Jobs

3+ years of experience building and maintaining production data pipelines.
Excellent English communication skills, both spoken and written, to effectively collaborate with cross-functional teams and mentor other engineers.
Clear writing is key in our remote-first setup.
Proficient in working with geospatial data and leveraging geospatial features.

💡 Responsibilities

Work with backend engineers and data scientists to turn raw data into trusted insights, handling everything from scraping and ingestion to transformation and monitoring.
Navigate cost-value trade-offs to make decisions that deliver value to customers at an appropriate cost.
Develop solutions that work in over 10 countries, considering local specifics.
Lead a project from concept to launch with a temporary team of engineers.
Raise the bar and drive the team to deliver high-quality products, services, and processes.
Improve the performance, data quality, and cost-efficiency of our data pipelines at scale.
Maintain and monitor the data systems your team owns.

AWS Docker Leadership PostgreSQL Python SQL Apache Airflow Cloud Computing Data Analysis ETL Git Kubernetes Apache Kafka Data engineering Data science Spark CI/CD Problem Solving RESTful APIs Mentoring Linux Excellent communication skills Teamwork Cross-functional collaboration Data visualization Data modeling Data management English communication

Posted 2 days ago

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🔥 Senior Analyst, Internal Audit - Data Scientist (L09)

Posted 2 days ago

📍 India

🧭 Full-Time

🔍 Internal Audit

🏢 Company: careers

🔧 Requirements

Minimum 3+ years of experience writing and optimizing SQL/SAS queries in a business environment or 5+ years of experience in lieu of a degree
Knowledge of data warehouse technical architecture, ETL and analytic tools in extracting unstructured and structured data
Experience in building algorithms and coding proficiency in Python is required
Experience with visualization software Tableau or Power BI
Experience managing, moving, and manipulating data from multiple sources
Familiar with segmentation techniques such as decision trees or k-means clustering
Familiar with model development techniques such as logistic regression, random forest, or gradient boosting
Ability to provide analytic support including pulling data, preparing analysis, interpreting data, making strategic recommendations, and presenting to client/product team
Ability to clearly explain technical and analytical information (verbally, written, and in presentation form) and summarize for key stakeholders
Outstanding communications, relationship building, influencing, and collaboration skills
Strong project management, communications, multi-tasking, ability to work independently

💡 Responsibilities

Deliver advanced analytics to support the audit plan, including cycle audits, issue validation, remediation activities and special projects
Design and deploy analytic scripts and dashboards to communicate actionable insights to audit stakeholders.
Document analytic results and findings into audit workpapers.
Ensure the accuracy and integrity of data used in audit engagements through data transformation techniques.
Deploy automation on repetitive audit tasks using data analytics and data engineering techniques.
Collaborate with Internal Audit teams to understand audit test objectives and data requirements.
Collaborate with remediation teams to ensure data insights are effectively integrated into action plans.
Lead projects from beginning to end, including ideation, data mining, strategy formulation, and presentation of results and recommendations.

Python SQL Data Analysis Data Mining ETL Excel VBA Machine Learning Numpy SAS EG Tableau Algorithms Data engineering Data science Pandas RESTful APIs MS Office Data visualization Data modeling

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🔥 Product Manager II

Posted 2 days ago

📍 US

💸 187000.0 - 232988.0 USD per year

🏢 Company: Pinterest Job Advertisements

🔧 Requirements

Master’s degree (or its foreign degree equivalent) in Data Science, Statistics, or closely related quantitative discipline and two (2) years of experience in the job offered or in any occupation in related field, OR Bachelor’s degree (or its foreign degree equivalent) in Data Science, Statistics or closely related quantitative discipline and five (5) years of progressively responsible experience in the job offered or in any occupation in related field.
Data Analysis
Software product management
Python
Impact evaluation
Strategic planning
Project management
A/B testing and Statistics
User experience research
Data processing

💡 Responsibilities

Work with engineers, user research, data scientists and the sales team to develop a deep customer understanding.
Lead product vision, strategy, technical development and execution for conversion visibility.
Develop clear product requirements and work with engineering, design, data analytics, product marketing, research teams and other product teams to deliver customer impact.
Communicate your strategy upward and outward internally to ensure you have the support and comprehension you need to be successful.

Project Management Python Data Analysis User Experience Design Data science A/B testing

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🔥 Graduate Summer Intern – AI/ML Software Developer

Posted 2 days ago

📍 United States

🧭 Internship

💸 43700.0 - 69900.0 USD per year

🔍 Software Development

🏢 Company: NREL

🔧 Requirements

Experience in deep learning models, Bayesian neural networks, graph neural network models, and probabilistic semantic graphs.
Experience in the formulation of mixed-integer optimization problems and open-source solvers for sensor placement in distribution systems.
Demonstrated experience in programming languages such as Python and MATLAB.
Experience with open-source, collaborative software development and use of tools such as GitHub or GitLab for project management and version control.

💡 Responsibilities

Contribute to the development of deep learning models such as Bayesian neural networks, graph neural networks, probabilistic semantic graphs, and Generative AI to detect anomalies such as missing data, bad data, and communications failure in sensor data.
Development of data driven forecasting and disaggregation models and validation of both centralized and distributed state estimation algorithms.

Python Software Development Data Analysis Image Processing Machine Learning Matlab C++Algorithms Data science Data Structures Data visualization

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🔥 Senior Data Scientist | CARE

Posted 2 days ago

📍 Portugal

🔍 Wellness

🔧 Requirements

Master’s degree or PhD in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
Proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or similar.
Strong understanding of generative AI architectures, including transformers and attention mechanisms.
Experience in multi-agent systems and LLMs.
Strong problem-solving abilities, with a focus on experimental design and data analysis.
Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
Have clear scientific thinking and a passion for integration R&D and cutting-edge technology into a product
Prior experience in Python and SQL a are mandatory requirements.

💡 Responsibilities

Understanding of state-of-the-art deep learning techniques, such as Transformers architectures and attention mechanisms, and knowledge of fine-tuning LLMs for enhanced model performance, using techniques such as LoRA, QLoRA, among others.
Design and implement structured function calling mechanisms within LLMs to enable dynamic interactions with APIs, databases, and retrieval-augmented generation (RAG) pipelines.
Craft clear instructions that help our models understand exactly what we need, creating reusable templates and testing against edge cases.
Preprocess, analyse, and curate high-quality datasets to train and fine-tune both embedding and generative models.
Develop robust evaluation frameworks to assess agentic AI performance, combining automated evaluation (LLM-as-judge), adversarial testing, human-in-the-loop evaluations, and custom behavioral metrics.
Establish monitoring systems that track LLM behavior in production, capturing key metrics around information retrieval, hallucinations, and latency.
Stay current with the latest research in generative AI,, share insights with the team, test promising approaches, and help make us better.
Collaborate with engineering teams to deploy models in scalable and efficient production environments.

AWS Python SQL Data Analysis Machine Learning PyTorch Data science

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🔥 Principal Engineer - Behaviors

Posted 2 days ago

📍 United States

💸 136500.0 - 266500.0 USD per year

🔍 Autonomous Vehicles

🔧 Requirements

BA, Masters or PhD in Machine Learning, Computer Science, Applied Mathematics, Statistics, Physics or a related field; or equivalent industry experience
In-depth understanding of common Machine Learning, Deep Learning algorithms, or ML Planning
Experience designing, training, and analyzing neural networks for at least one of the following applications: object detection, semantic/instance segmentation, visual classification, motion/gesture recognition, sensor fusion, multitask learning, motion prediction, and/or multi-object tracking
Advanced knowledge of software engineering principles including software design, source control management, build processes, code reviews, testing methods
Fluency in Python, including standard scientific computing libraries and Python bindings development experience
Experience with PyTorch or other deep learning frameworks
Experience working with large data sets and deriving insights from data
Effectiveness at leading and executing large, complex technical initiatives

💡 Responsibilities

Define and influence the direction of the team, organization, and/or department.
Advise leaders on technology problems and solutions
Connect and drive business impact through technology solutions
Formulate problems, architect solutions, and design processes
Prototype, evaluate, implement, and iterate on solutions
Pioneer research into state of the art solutions and systems for autonomous vehicles
Productionize and deploy solutions onto autonomous vehicle fleets
Mentor and grow junior and experienced engineers and researchers
Help create and reinforce a culture of inclusion, innovation, and excellence

Python Software Development Data Analysis Git Image Processing Machine Learning PyTorch C++Algorithms Data science Software Engineering

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🔥 Machine Learning Engineer

Posted 3 days ago

📍 England, Scotland, Portugal, Poland, Spain

🔍 Robotics

🏢 Company: Locus Robotics👥 251-500💰 $117,000,000 Series F over 2 years agoWarehousing Logistics Industrial Automation E-Commerce Warehouse Automation Robotics

🔧 Requirements

4+ years of hands-on experience designing and deploying machine learning models in production, with a focus on reinforcement learning (RL) and multi-agent systems (MAS).
Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code.
Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows.
Experience working with Polars and/or Pandas for high-performance data processing.
Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization and orchestration using Docker and Kubernetes.
Hands-on experience with reinforcement learning frameworks such as OpenAI Gym or Stable-Baselines3.
Practical knowledge of optimization algorithms and probabilistic modeling techniques.
Experience integrating models into real-time decision-making systems or multi-agent RL environments (MARL).

💡 Responsibilities

Utilize, develop, and enhance simulation tooling and infrastructure.
Develop, deploy, and maintain machine learning models, with a strong focus on reinforcement learning (RL) and multi-agent systems (MAS).
Implement and improve MLOps pipelines.
Collaborate with data engineers and software developers to ensure seamless integration of machine learning models with existing infrastructure and data pipelines.
Stay up to date with advancements in reinforcement learning, distributed computing, and ML frameworks to drive innovation in the organization.
Work with cloud-based solutions (AWS, GCP, or Azure) to deploy and manage machine learning workloads in a scalable manner.

AWS Docker Python SQL Cloud Computing Data Analysis Kubernetes Machine Learning PyTorch Algorithms Data science Pandas Tensorflow

Posted 3 days ago

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🔥 Engineer III - ML Platform (Remote, IND)

Posted 3 days ago

📍 India

🧭 Full-Time

🔍 Cybersecurity

🏢 Company: crowdstrikecareers

🔧 Requirements

3+ years experience developing and deploying machine learning solutions to production. Familiarity with typical machine learning algorithms from an engineering perspective (how they are built and used, not necessarily the theory); familiarity with supervised / unsupervised approaches: how, why, and when and labeled data is created and used
3+ years experience with ML Platform tools like Jupyter Notebooks, NVidia Workbench, MLFlow, Ray, Vertex AI etc.
Experience building data platform product(s) or features with (one of) Apache Spark, Flink or comparable tools in GCP. Experience with Iceberg is highly desirable.
Proficiency in distributed computing and orchestration technologies (Kubernetes, Airflow, etc.)
Production experience with infrastructure-as-code tools such as Terraform, FluxCD
Expert level experience with Python; Java/Scala exposure is recommended. Ability to write Python interfaces to provide standardized and simplified interfaces for data scientists to utilize internal Crowdstrike tools
Expert level experience with CI/CD frameworks such as GitHub Actions
Expert level experience with containerization frameworks
Strong analytical and problem solving skills, capable of working in a dynamic environment
Exceptional interpersonal and communication skills. Work with stakeholders across multiple teams and synthesize their needs into software interfaces and processes.

💡 Responsibilities

Help design, build, and facilitate adoption of a modern Data+ML platform
Modularize complex ML code into standardized and repeatable components
Establish and facilitate adoption of repeatable patterns for model development, deployment, and monitoring
Build a platform that scales to thousands of users and offers self-service capability to build ML experimentation pipelines
Leverage workflow orchestration tools to deploy efficient and scalable execution of complex data and ML pipelines
Review code changes from data scientists and champion software development best practices
Leverage cloud services like Kubernetes, blob storage, and queues in our cloud first environment

Python Data Analysis GCP Kubernetes Machine Learning MLFlow Airflow Data engineering Data science Spark CI/CD RESTful APIs Terraform

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Why Remote Data Science Jobs Are Becoming More Popular

The remote work from home is increasingly in demand among computer and IT professionals for several reasons:

Flexibility in time and location.
Collaboration with international companies.
Higher salary levels.
Lack of ties to the office.

Remote work opens up new opportunities for specialists, allowing them to go beyond geographical limits and build a successful remote IT career. This employment model is transforming traditional work approaches, making it more convenient, efficient, and accessible for professionals worldwide.

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