Remote Data Science Jobs

Data Science

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34 jobs found.

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🔥 Data Science & AI Specialist

Posted about 18 hours ago

📍 United States, Canada

🧭 Full-Time

🔍 Digital Product Engineering

🔧 Requirements

8+ years in engineering and machine learning
4+ years in AI/ML solutions for business applications
Experience with key LLM models APIs and frameworks

💡 Responsibilities

Develop and deploy AI/ML/Gen AI solutions
Work with large structured & unstructured datasets
Implement RAG systems and knowledge graphs

Python SQL Machine Learning Data engineering Data science FastAPI Nosql React Microservices

Posted about 18 hours ago

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🔥 Senior Data Science Engineer 2

Posted 7 days ago

📍 United States

🧭 Full-Time

💸 160000.0 - 215000.0 USD per year

🔍 Cybersecurity

🏢 Company: SimSpace👥 251-500💰 $45,000,000 about 1 year agoSecurity Cyber Security Network Security Software

🔧 Requirements

6+ years of professional Data Science experience or a PhD
Familiarity with machine learning topics and libraries
Proficient in Python and git
Experience with SQL and NoSQL databases

💡 Responsibilities

Enhance cybersecurity assessments
Conduct evaluation of cybersecurity tool logs
Create and analyze large-scale datasets
Improve scoring algorithms and automate processes

Python SQL Data Analysis Git Machine Learning Numpy PyTorch Algorithms Nosql Pandas Tensorflow CI/CD

Posted 7 days ago

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🔥 Director, Data Science

Posted 7 days ago

📍 United States

💸 208000.0 - 235000.0 USD per year

🔍 Sports gaming

🏢 Company: Underdog Sports

🔧 Requirements

10+ years of experience in data science, with 4+ years in a leadership role.
Proven expertise in building and deploying machine learning models, including at least one or more of LTV, churn prediction, MMM, and recommender systems.
Strong understanding of personalization techniques and strategies.
Proficiency in Python, R, SQL, and modern machine learning frameworks.
Ability to lead and inspire a team, fostering a culture of collaboration and professional growth.
Strong communication skills with the ability to convey complex ideas to technical and non-technical audiences.
A strategic thinker who aligns data science initiatives with business objectives.

💡 Responsibilities

Lead and mentor a team of data scientists, fostering a collaborative and high-performing culture.
Develop predictive models, including customer LTV, churn prediction, MMM, and propensity models, ensuring they drive measurable business outcomes.
Build and refine recommender systems to personalize CRM communications, promotions, and in-app user experiences.
Work closely with engineering teams to productionize models and integrate them into existing workflows.
Partner with product, marketing, and CRM teams to design and implement data-driven personalization strategies.
Act as a thought partner to stakeholders across the business, translating complex data science problems into actionable insights.
Stay informed on industry trends and emerging techniques in data science and machine learning.
Promote best practices in model development, validation, and monitoring to ensure accuracy and reliability.

Leadership Python SQL ETL Machine Learning Numpy People Management Data science Pandas Tensorflow Communication Skills Analytical Skills Mentoring Data visualization Team management Strategic thinking Data modeling Data analytics

Posted 7 days ago

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🔥 Data Science Manager, Styling Algorithms

Posted 8 days ago

📍 United States

🧭 Full-Time

💸 153700.0 - 226000.0 USD per year

🔍 Fashion Technology, Data Science

🏢 Company: Stitch Fix👥 5001-10000💰 $11,850,773 over 7 years ago🫂 Last layoff 10 months agoE-Commerce Retail Fashion Apparel

🔧 Requirements

5+ years of experience in machine learning and data science
At least 2 years in a leadership role
Experience with A/B testing and performance metrics
Familiarity with cloud-based infrastructure

💡 Responsibilities

Directly shape product strategy using data-driven insights
Drive business impact through improved personalization
Lead team building transformative algorithm capabilities
Collaborate with stakeholders to define key metrics
Oversee algorithm development lifecycle
Manage prioritization and execution of key projects
Implement best practices for collaboration and quality
Stay updated with AI and machine learning trends
Foster a growth-oriented culture within the team
Establish vision and roadmap for styling algorithms

Cloud Computing Data Analysis Machine Learning Data science A/B testing

Posted 8 days ago

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🔥 Senior Manager Data Science

Posted 9 days ago

📍 United States

💸 196930.0 - 238500.0 USD per year

🔍 EdTech

🏢 Company: Coursera Sourcing

🔧 Requirements

6+ years of experience in data analytics, business intelligence, or related roles, with 4+ years of managerial experience.
Strong command of analytical and visualization tools including Amplitude, Looker, SQL, and Python for data analysis and modeling.
Excellent knowledge of Statistics, Experimentation, Test Design Setup, Measurement and A/B Testing.
Demonstrated experience in leading cross-functional projects and collaborating with stakeholders at all levels of the organization.

💡 Responsibilities

Partner with stakeholders to establish metrics and goals to drive growth product and monetization strategies.
Collaborate closely with stakeholders to drive development data-driven strategies and inform investment decisions to support growth and optimization for Grow with Google.
Increase self-service to insights capabilities via a combination of tools, dashboards, and education.
Lead the data science and analytics organization to always push the boundaries to deliver high quality analysis and translate data into insights, strategies and actions that can help Coursera’s business growth; grow the organization, mentor and maintain a high bar of analytical depth for the team.

Python SQL Data Analysis ETL Machine Learning Amplitude Analytics Data science Communication Skills Analytical Skills Mentoring Cross-functional collaboration Data visualization Strategic thinking Data modeling A/B testing

Posted 9 days ago

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🔥 Head of Data Science and Analytics

Posted 14 days ago

📍 US

🧭 Fulltime

💸 230000.0 - 270000.0 USD per year

🔍 Web3, NFT marketplace, Bitcoin dApp

🏢 Company: Magic Eden👥 51-100💰 $500,000 ICO over 2 years ago🫂 Last layoff about 2 years agoInternet Cryptocurrency Marketplace Web3

🔧 Requirements

8+ years of experience in data science, analytics, and business intelligence with at least 3+ years leading high-performing data teams.
Experience in a high-growth consumer technology startup environment required, ideally in crypto or fintech
Proven ability to connect data insights to business strategy, driving measurable impact on growth, retention, and revenue.
Deep understanding of data science methodologies, analytics frameworks, and modern data infrastructure. Familiarity with SQL, Python, and data visualization tools is a plus.
Experience working closely with product, engineering, marketing, and leadership teams to align data initiatives with company goals.
Ability to build scalable data processes, improve execution, and ensure high-quality insights are delivered efficiently.
Experience in hiring, mentoring, and developing data teams. Track record of fostering a culture of learning, feedback, and continuous improvement.
Ability to navigate ambiguity, synthesize complex data, and create clear, actionable strategies that drive business results.
Hands-on approach with the ability to contribute as an individual contributor when needed

💡 Responsibilities

Drive Strategic Impact: Identify high-value opportunities where data can drive growth, revenue, and retention. Ensure insights shape company and product strategy, leading to measurable improvements in key metrics.
Develop Operational Excellence: Build scalable systems and processes for data workflows, ensuring the timely and high-quality delivery of insights. Establish best practices that improve efficiency and execution.
Lead Cross-Functional Collaboration: Partner with product, engineering, and marketing teams to embed data into decision-making and align initiatives with business priorities. Foster a culture where data is a core part of strategic discussions.
Build and Grow a High-Performing Team: Recruit, mentor, and retain top data talent. Establish a strong team culture focused on learning, feedback, and continuous improvement. Ensure the team is engaged, effective, and seen as a key driver of business success.
Establish a Scalable Data Culture: Ensure data is deeply integrated into company operations. Create processes that enable teams across the organization to leverage insights effectively and make data-driven decisions at every level.

AWS Leadership Python SQL Business Intelligence Cloud Computing Data Analysis ETL Machine Learning People Management Product Management Cross-functional Team Leadership Data engineering Data science Strategic Management RESTful APIs Data visualization Data modeling Data management A/B testing

Posted 14 days ago

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🔥 Data Science Engineer

Posted 14 days ago

🔍 Software Development

🔧 Requirements

8+ years of experience in engineering, machine learning & LLMs
4+ years of hands-on experience in building & deploying AI/ML/Gen AI solutions in large business critical applications
2+ years of experience in developing Gen AI products using variety of LLMs & frameworks
Advanced proficiency in Python for data science, engineering & LLMs
Experience with leveraging, training and fine-tuning Foundation Models including multimodal inputs and outputs
Strong experience working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex)
Proficiency in generating and working with embeddings across variety of data formats
Expertise with RAG concepts and fundamentals (vectorDBs, semanticsearch, re-rankers etc)
Experience with multi-agent frameworks/systems
Experience in working with variety of data bases (SQL, no SQL), APIs & microservices development
Experience with LLMOps tools (e.g. Langsmith) to implement guardrails, track accuracy, hallucinations, bias and other metrics in Gen AI products
Experience in constructing and querying knowledge graphs including graph-based reasoning

💡 Responsibilities

Building & deploying AI/ML/Gen AI solutions in large business critical applications.
Developing Gen AI products using variety of LLMs & frameworks.
Working with large structured & unstructured datasets and deploy AI/ML/Gen AI solutions through automated pipelines.
Leveraging, training and fine-tuning Foundation Models including multimodal inputs and outputs.
Working with key LLM models APIs (e.g. OpenAI, Anthropic) and LLM Frameworks (e.g. LangChain, LlamaIndex).
Generating and working with embeddings across variety of data formats.
Implementing RAG systems that combine knowledge bases.
Working with variety of data bases (SQL, no SQL), APIs & microservices development.
Implementing guardrails, track accuracy, hallucinations, bias and other metrics in Gen AI products using LLMOps tools (e.g. Langsmith).
Constructing and querying knowledge graphs including graph-based reasoning.
Experience in multi-agent frameworks/systems and an understanding of multi-agent systems and their applications in complex problem-solving scenarios.

Posted 14 days ago

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🔥 Google Cloud AI & Data Science Engineer (Dialogflow, Vertex AI, & Multimodal AI)

Posted 15 days ago

📍 Cyprus, Greece, Spain

🔍 SaaS

🏢 Company: Bolsterup

🔧 Requirements

3+ years of hands-on experience with Dialogflow CX, including complex conversation flows, fulfillment, and webhook integrations.
Strong expertise in Vertex AI (model training, fine-tuning, LLMs, embedding techniques, and API usage).
Experience in data science, statistical modeling, and machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn.
Solid experience with Google Cloud Platform (GCP) services such as Cloud Functions, Cloud Run, Pub/Sub, and BigQuery.
Experience designing production-ready AI services, including API gateways, databases, job batching, and cloud-based workflows.
Proficiency in Python or Node.js for AI integration, data processing, and backend development.
Expertise in handling large unstructured datasets, including natural language processing (NLP), computer vision, and deep learning.
Understanding of AI ethics, bias reduction, and responsible AI deployment.
Experience working with RESTful APIs, GraphQL, and third-party AI integrations.
Knowledge of multimodal AI (text, speech, image, and video processing) within Google AI systems.
Strong problem-solving skills, with the ability to optimize AI models for performance and scalability.

💡 Responsibilities

Develop & Optimize AI Agents: Design and implement AI-driven conversational experiences using Dialogflow CX, integrating with Vertex AI for advanced NLP, LLM capabilities, and multimodal interactions.
Custom AI Model Training & Data Science: Develop and train custom AI models using structured and unstructured data, leveraging Vertex AI, TensorFlow, PyTorch, and AutoML.
Data Processing & Analysis: Work with large-scale datasets, performing data preprocessing, feature engineering, and AI-driven insights generation.
Cloud Architecture & Deployment: Architect scalable AI solutions within Google Cloud Platform (GCP), ensuring high availability, performance, and cost efficiency.
Production-Ready AI Services: Design and deploy scalable and efficient AI services, including setting up API gateways, databases, job batching systems, and cloud-based service layers.
Multimodal AI Capabilities: Build AI solutions that process text, speech, image, and video data, integrating APIs and Google’s AI agent ecosystem.
AI-Driven Insights & Predictive Analytics: Apply machine learning techniques for predictive analytics, recommendation systems, and anomaly detection.
API Development & Integration: Develop backend services and APIs to integrate AI models with customer applications, ensuring seamless data flow.
Infrastructure & Resource Management: Set up and maintain serverless and containerized deployments, including Cloud Run, Kubernetes, and managed database solutions.
Testing & Validation: Implement automated testing, model validation, and AI evaluation frameworks to ensure accuracy and responsiveness.
Security & Compliance: Ensure AI models comply with data privacy regulations (GDPR, HIPAA, etc.) and industry best practices.
Collaboration & Documentation: Work closely with product managers, developers, and stakeholders to align AI implementations with business objectives. Maintain detailed documentation of AI workflows, architectures, and model training processes.

Docker GraphQL Node.js Python GCP Kubernetes Machine Learning PyTorch Data science Tensorflow RESTful APIs

Posted 15 days ago

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🔥 Data Science Role with IFRS9 modelling

Posted 17 days ago

📍 Canada

🧭 Full-Time

🔍 Data Science

🔧 Requirements