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Data science

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373 jobs found.

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🔥 Data & AI Engineer (Frankfurt, Germany)

Posted about 8 hours ago

📍 Germany

🔍 AI and data analytics consulting

🏢 Company: Unit8 SA

🔧 Requirements

MSc level in the field of Computer Science, Machine Learning, Applied Statistics, Mathematics, or equivalent work experience.
Proficient software engineer who has experience in applying a blend of software engineering, machine learning, and statistical methods to solve real-world business problems
Proficient in one of the following languages: Python, Scala, Java.
Experience with cloud technologies is a strong plus.

💡 Responsibilities

Work with our customers to understand their challenges, design and implement solutions.
Closely collaborate with other data scientists, software engineers and business stakeholders.
Evaluate, compare and present results to technical and non-technical audience.
Contribute to the implementation and engineering of systems at different scales: from small proof-of-concepts to larger end-to-end data systems.
Implement best practices in CI/CD

AWS Docker Python SQL Cloud Computing Data Analysis ETL Java Kubernetes Machine Learning Algorithms Data engineering Data science Spark CI/CD RESTful APIs Scala Software Engineering

Posted about 8 hours ago

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🔥 Senior Machine Learning Engineer

Posted about 8 hours ago

📍 USA

🧭 Full-Time

🔍 Audit and advisory

🏢 Company: Fieldguide👥 101-250💰 $30,000,000 Series B 12 months agoArtificial Intelligence (AI)Document Management

🔧 Requirements

4-5 years of experience in applied machine learning or related field
Strong proficiency in Python and its ML/data science libraries
Extensive experience with NLP techniques and generative AI technologies
Experience with LLMs and both text-to-text and text-to-image generative models
Proficiency in working with large datasets and creating ETL processes
Experience with version control systems (e.g., Git) and CI/CD practices
Ability to work in a fast-paced, changing startup environment

💡 Responsibilities

Collaborate with stakeholders to identify and map business problems to ML solutions
Design, develop, and implement ML models with a focus on NLP and generative AI applications
Curate, clean, and prepare data for model development and training
Create and maintain ETL jobs for data processing
Conduct rapid prototyping of ML solutions to quickly iterate on ideas
Stay current with the latest advancements in ML, particularly in NLP and generative AI
Collaborate with the platform engineering team to integrate ML solutions into the overall product architecture
Implement data flywheels to continuously improve ML features through increased usage
Define and implement ML performance metrics
Contribute to the product roadmap with ML-driven feature ideas
Be an essential technical contributor at a Series B-stage company as it scales

AWS Python SQL ETL Git Machine Learning Numpy Data science Pandas Tensorflow CI/CD A/B testing

Posted about 8 hours ago

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🔥 Machine Learning Engineer (LLMs)

Posted about 9 hours ago

📍 Poland

🧭 Full-Time

💸 23500.0 - 35000.0 PLN per month

🔍 Education Technology

🏢 Company: Brainly👥 251-500💰 $80,000,000 Series D about 4 years ago🫂 Last layoff over 2 years agoEducation EdTech Communities E-Learning Apps Social Network Peer to Peer Software

🔧 Requirements

3+ years experience with deployment and maintenance of Machine Learning models in production
Experience in deploying and maintaining Deep Learning models, particularly Large Language Models (LLMs)
Strong command of writing production-level code in Python, with a focus on best engineering practices, in particular for training & deploying models.
PyData stack along with quick frontend frameworks e.g. streamlit.
Proven expertise in Cloud Computing (preferably AWS and services like IAM, EC2, S3, ECR, EKS, Redshift, Athena, Glue, Lambda, SecretManager) for storage, data pipelines, ML pipelines, and ML deployment.
Machine Learning frameworks such as: Tensorflow, PyTorch, JAX, scikit-learn, Transformers (HuggingFace).
Proven track record of development of data and machine learning pipelines.
Knowledge of Linux/Unix system, shell scripting.
Parallel computing (multi-processing, async, GPUs, types of AI parallelism).
Culture of DevOps and high-quality software standards.
Fluency in English.

💡 Responsibilities

Operationalization of Machine Learning Models
Orchestration of the entire ML model lifecycle, from development and deployment to monitoring, maintenance, and optimization ensuring scalability, efficiency, and reliability.
Implementation of automated workflows for model retraining, versioning, and performance tracking to ensure long-term stability.
Transformation of Machine Learning artifacts into production systems and services maintaining robust integration with existing engineering infrastructure.
Tooling, Infrastructure & Experimentation Support
Design and implementation of tools, frameworks, and infrastructure to enhance efficiency of Data Scientists and other stakeholders simplifying areas such as model training and evaluation, data annotation, and processing.
Working with large-scale datasets in structured and ad-hoc exploratory setups to support both creation of well-organized data pipelines and rapid experimentation and prototyping.
Supporting Technical Lead and Data Scientists in refactoring and optimizing research code, ensuring high-quality, reusability, and scalability of delivered solutions bridging the gap between AI experimentation and real-world deployment.
Continuous Learning
Staying up to date with cutting-edge advancements in AI technology, including state-of-the-art models, algorithms, tools, and frameworks (both models/algorithms and tools/libraries/SaaS/APIs, etc.).
Exploring opportunities to incorporate new methodologies, libraries, and services that enhance Brainly’s AI capabilities.

AWS Python SQL Bash Cloud Computing Kubernetes Machine Learning PyTorch Data science REST API Tensorflow CI/CD Linux DevOps Microservices

Posted about 9 hours ago

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🔥 Lead Machine Learning Scientist, Personalisation

Posted about 10 hours ago

📍 United Kingdom

🧭 Full-Time

💸 105000.0 - 140000.0 GBP per year

🔍 Financial Technology

🏢 Company: Monzo👥 1001-5000💰 Secondary Market 5 months ago🫂 Last layoff almost 5 years agoFinancial Services Banking Wealth Management FinTech

🔧 Requirements

Multiple year track record of excellence leading the development and deployment of advanced Machine Learning models to tackle real business problems preferably in a fast moving tech company
Experience developing and shipping state of the art ML architectures to production and delivering business impact
Extensive experience writing production Python code and a strong command of SQL. You are comfortable using them every day, and keen to learn Go lang which is used in many of our backend microservices

💡 Responsibilities

Working with stakeholders across the organization to identify and scope out the most impactful opportunities to tackle business problems in personalisation.
Leading the design and development of advanced real time Machine Learning models, for example exploring how recent advances in machine learning (neural network, graph-based, and sequence-based architectures, LLMs) can drive improvements in our ability to deliver personalised user experiences.
Providing technical leadership to drive up levels of technical expertise and best practice across the Machine Learning discipline, leading by example and mentoring others.
Working closely with our ML platform team to steer the ongoing development of tools to enable rapid iteration of models and optimisations of the full ML model lifecycle.

Leadership Python SQL Cloud Computing Data Analysis Machine Learning Algorithms API testing Data science RESTful APIs Microservices Data modeling

Posted about 10 hours ago

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🔥 Senior Product Manager, New Products

Posted about 11 hours ago

📍 United States

💸 175000.0 - 195000.0 USD per year

🔍 B2B healthcare

🏢 Company: SmarterDx👥 101-250💰 $50,000,000 Series B 10 months agoArtificial Intelligence (AI)Hospital Information Technology Health Care

🔧 Requirements

5+ years of product management experience in B2B healthcare, ideally in automation, AI-driven workflows, or revenue cycle management.
Proven ability to launch 0 to 1 products, scale and mature a product platform, balancing technical constraints with user needs.
Experience working cross-functionally with engineering, data science, and UX teams to drive product success.
Experience working directly with customers.
Experience working with healthcare data products and using data visualization to drive user decisions.

💡 Responsibilities

Own and scale the Denials product, defining its strategy, roadmap, and execution.
Roll up your sleeves and ruthlessly prioritize features based on user needs, market demand, and commercial impact.
Identify opportunities to improve automation, streamline workflows, and enhance usability for appeal writers.
Work closely with engineering, data science, and design to translate AI predictions into real-world user value.
Define, track, and report on key success metrics to measure product performance and adoption.
Communicate clearly with stakeholders, ensuring alignment across product, sales, and customer success teams.
Write and standardize product and technical documentation, modeling strong project management best practices.

SQL Agile Artificial Intelligence Business Analysis Data Analysis Machine Learning Product Management QA User Experience Design Cross-functional Team Leadership Product Development Data science REST API Strategic Management CI/CD Data visualization Stakeholder management

Posted about 11 hours ago

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🔥 Data Engineer

Posted about 16 hours ago

📍 United States

🧭 Full-Time

🔍 Sustainable Agriculture

🏢 Company: Agrovision

🔧 Requirements

Experience with RDBMS (e.g., Teradata, MS SQL Server, Oracle) in production environments is preferred
Hands-on experience in data engineering and databases/data warehouses
Familiarity with Big Data platforms (e.g., Hadoop, Spark, Hive, HBase, Map/Reduce)
Expert level understanding of Python (e.g., Pandas)
Proficient in shell scripting (e.g., Bash) and Python data application development (or similar)
Excellent collaboration and communication skills with teams
Strong analytical and problem-solving skills, essential for tackling complex challenges
Experience working with BI teams and tooling (e.g. PowerBI), supporting analytics work and interfacing with Data Scientists

💡 Responsibilities

Collaborate with data scientists to ensure high-quality, accessible data for analytical and predictive modeling
Design and implement data pipelines (ETL’s) tailored to meet business needs and digital/analytics solutions
Enhance data integrity, security, quality, and automation, addressing system gaps proactively
Support pipeline maintenance, troubleshoot issues, and optimize performance
Lead and contribute to defining detailed scalable data models for our global operations
Ensure data security standards are met and upheld by contributors, partners and regional teams through programmatic solutions and tooling

Python SQL Apache Hadoop Bash ETL Data engineering Data science RDBMS Pandas Spark Communication Skills Analytical Skills Collaboration Problem Solving Data modeling

Posted about 16 hours ago

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🔥 Senior Data Analyst, Revenue

Posted about 17 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Givebutter👥 101-250💰 $50,000,000 Series A 11 months agoNon Profit Event Management Software

🔧 Requirements

Advanced degree in Statistics, Computer Science, Mathematics or a related field, or relevant industry experience.
Expert querying and data manipulation skills using SQL, and strong data analysis skills using Python (or any other statistical programming language)
Experience in Marketing Analytics, Sales Analytics, or similar.

💡 Responsibilities

Manage the inflow of data requests from revenue stakeholders, ensuring adequate two-way communication on needs, expectations, and progress, and high quality, timely delivery.
Drive the strategic roadmap of Revenue Analytics as the business grows and data needs scale in both magnitude and complexity.
Be the subject matter expert in the customer funnel, driving and developing the company’s understanding of acquisition, conversion, engagement, and retention through behavioral analyses and insights.

Python SQL Data Analysis ETL Machine Learning API testing Data engineering Data science Communication Skills Analytical Skills Collaboration Problem Solving Data visualization Data modeling Data analytics Data management Customer Success

Posted about 17 hours ago

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🔥 AI Curriculum Architect (Remote)

Posted about 17 hours ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: TechSmart👥 11-50 Virtual Reality Electronics Lifestyle News Hardware

🔧 Requirements

Minimum of 3-5 years of professional experience in software engineering, with a focus on Python, web development, data science or AI applications
At least 3-5 years of experience in programming or software development instruction and/or curriculum development
Expertise in Python programming, including knowledge of libraries and frameworks commonly used in data science, AI and machine learning.
Proficiency with HTML, CSS, and JavaScript, including knowledge of libraries and frameworks commonly used for developing web-based applications.
Strong foundational knowledge understanding of AI concepts and their practical applications
Experience working with prompt engineering, generative AI technologies and tools.
Ability to design comprehensive curricula that align with educational standards and strategic objectives.
Proficiency in creating detailed lesson plans, learning activities, and assessments that cater to diverse learning styles.

💡 Responsibilities

Collaborate with the CEO and Product Manager to develop a curriculum roadmap.
Lead the research, analysis, and design of new courses, as well as enhancements to existing courses.
Lead instructional design of the curriculum.
Develop curriculum standards, documentation, and lesson activity prototypes.
Design and implement streamlined, AI-driven curriculum development workflows.
Contribute directly to curriculum asset production as needed.
Collaborate closely with the CTO to define technical requirements and design platform features.

Python Artificial Intelligence HTML CSS Javascript Machine Learning Algorithms Data science Data Structures Software Engineering

Posted about 17 hours ago

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🔥 Sr. Data Scientist

Posted 1 day ago

📍 United States

🧭 Full-Time

🔍 Software Development

🏢 Company: Measured👥 101-250💰 $21,000,000 almost 3 years agoSaaS Analytics

🔧 Requirements

5+ years of experience in data science, with a focus on marketing analytics, econometrics, or causal inference with 2+ years of direct experience in building MMMs or marketing attribution.
B.S. or higher in Mathematics, Computer Science, Statistics, Data Science, or a related quantitative field.
Strong expertise in Marketing Mix Modeling (MMM), marketing attribution, or media measurement.
Proficiency in Python, SQL, and statistical modeling techniques such as Bayesian inference, time-series forecasting, and causal inference.
Experience working with large-scale data, experimentation, and probabilistic modeling.
Strong problem-solving skills, with an ability to work independently in a fast-moving environment.
Excellent communication skills, with the ability to translate mathematical concepts into business insights for technical and non-technical audiences.
Ability to integrate and debug complex code, ensuring models operate reliably at scale.
Ability to communicate complex mathematical concepts to any audience.
Ability to integrate and debug complex code.
Independent decision maker. Can take calculated risks and deal with ambiguity.
Takes initiative to improve and try new things.
Ability to work independently with minimal supervision within a strong team environment.
Comfortable with rapid change.
Values diversity and integrity.

💡 Responsibilities

Develop and refine advanced MMM models, incorporating media variables, pricing indices, promotional schedules, holidays, macroeconomic factors, and causal inference signals.
Implement Bayesian inference, hierarchical models, and experimental design techniques to enhance MMM accuracy and insights.
Automate and optimize model training, deployment, and monitoring to support large-scale, high-frequency modeling across clients.
Collaborate with Product and Engineering teams to integrate advanced data science solutions into the Measured platform.
Interpret complex data science outputs and translate them into actionable recommendations for marketers.
Conduct R&D on emerging measurement methodologies and apply cutting-edge statistical and machine learning techniques.
Support internal teams by providing expertise on MMM results, ensuring high confidence in model outputs and business recommendations.

AWS Python SQL Data Analysis Machine Learning Data science Communication Skills Problem Solving Cross-functional collaboration Data visualization Data modeling

Posted 1 day ago

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🔥 Staff Technical Enablement Specialist

Posted 1 day ago

📍 United States

💸 123000.0 - 235900.0 USD per year

🔍 Data/AI

🔧 Requirements

7+ years of experience in technical pre-sales, technical enablement, technical program management, or consulting with a focus on data, AI, or cloud technologies.
Experience building, delivering, and scaling technical enablement programs for highly skilled technical teams.
Proven ability to create, manage, and execute large-scale enablement programs, balancing technical rigor with structured program management.
Exceptional communication and presentation skills, with the ability to engage technical and executive audiences.
Strong stakeholder management and collaboration skills, with the ability to align multiple teams toward a common goal.
[Preferred] Experience in technical pre-sales roles, building proofs-of-concept, or implementing technical solutions for customers.
[Preferred] Databricks certification or experience with Apache Spark™, MLflow, Delta Lake, and other open-source technologies.

💡 Responsibilities

Design, implement, and scale enablement solutions that foster domain specialization, hands-on expertise, and technical mastery.
Introduce innovative multi-signal validation methods that assess expertise through real-world application and structured learning.
Facilitate enablement sessions, workshops, and hands-on activities that reinforce applied problem-solving and deep technical skills.
Develop and maintain technical content, including reference architectures, solution guides, and POC templates.
Measure impact and iterate on enablement programs, leveraging feedback and performance data to drive improvements.
Collaborate with technical field teams, enablement leaders, and stakeholders to continuously refine and scale high-impact training programs.
Drive adoption of enablement programs and strategies among senior leaders by proposing solutions that align with business priorities, address key challenges, and incorporate industry trends.

AWS Python SQL Artificial Intelligence Cloud Computing ETL Machine Learning MLFlow Cross-functional Team Leadership API testing Data engineering Data science REST API Communication Skills Data visualization Stakeholder management Data analytics

Posted 1 day ago

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