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Data science

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🔥 Grupo QuintoAndar | Tech Lead Manager (AI Core Platform)

Posted about 8 hours ago

📍 Brazil

🧭 Full-Time

🔍 Software Development

🏢 Company: Grupo QuintoAndar

🔧 Requirements

Solid understanding of the engineering challenges of deploying machine learning systems to production;
Solid understanding of systems, software and data engineering best practices;
Proficiency with cloud-based services;
Proficiency in Python or another major programming language;
Have experience building backend systems, event driven architectures and rest/http applications
Have experience building solutions with LLMs (RAG, fine-tuning);
Have experience building AI agents and AI powered applications, familiarity with agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI);
Experience leading teams and managing careers.

💡 Responsibilities

Lead a small team of Data Scientists and Machine Learning Engineers to build solutions based on AI/ML.
Be a technical reference to the team, including doing hands-on engineering work.
Shaping the technical direction of our products, translating business requirements into solutions.
Discuss business requirements with the Product Manager and other stakeholders.

AWS Backend Development Docker Leadership Project Management Python Software Development SQL Artificial Intelligence Cloud Computing Kubernetes Machine Learning Software Architecture Algorithms Data engineering Data science Data Structures REST API Communication Skills CI/CD Agile methodologies RESTful APIs Excellent communication skills Problem-solving skills Team management Technical support Data modeling

Posted about 8 hours ago

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🔥 Grupo QuintoAndar | Tech Lead Manager (AI Core Platform)

Posted about 8 hours ago

📍 Portugal

🧭 Full-Time

🔍 Real Estate Tech

🏢 Company: Grupo QuintoAndar

🔧 Requirements

Solid understanding of the engineering challenges of deploying machine learning systems to production
Proficiency with cloud-based services
Proficiency in Python or another major programming language
Have experience building backend systems, event driven architectures and rest/http applications
Have experience building solutions with LLMs (RAG, fine-tuning)
Have experience building AI agents and AI powered applications, familiarity with agentic frameworks (LangGraph, LangChain, AutoGen, CrewAI)

💡 Responsibilities

Lead a small team of Data Scientists and Machine Learning Engineers to build solutions based on AI/ML.
Be a technical reference to the team, including doing hands-on engineering work.
Shaping the technical direction of our products, translating business requirements into solutions.
Discuss business requirements with the Product Manager and other stakeholders.

AWS Backend Development Docker Leadership Python Software Development SQL Apache Airflow Cloud Computing Flask Kubernetes Machine Learning Numpy Data engineering Data science RDBMS REST API Pandas Communication Skills CI/CD RESTful APIs

Posted about 8 hours ago

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🔥 IT Content Author

Posted about 9 hours ago

📍 United States

💸 74300.0 - 106567.0 USD per year

🔍 IT

🏢 Company: wiley_careers

🔧 Requirements

Typically has MS/PhD or equivalent experience to demonstrate subject matter expertise
Typically has at least 2 years teaching experience, usually more
Acts as a resource for colleagues with less experience
Requires in-depth knowledge and experience
Uses best practices and knowledge of internal or external business issues to improve processes
Solves complex problems; takes a new perspective using existing solutions
Works independently, with guidance in only the most complex situations
Progression to this level is typically restricted to selected job families based on business requirements

💡 Responsibilities

May train/mentor for new authors in discipline
Authors sections, CA’s, labs, and other content types independently.
Takes ownership of assigned projects/titles.
May serve as a lead author on one or more titles
May maintain backlog of improvements for given titles and contributes strategy and roadmap ideas to leads or Senior Managers.
Responsible for ensuring quality of their projects/titles along with the project manager.
May speak at conferences; publish research papers, articles and blog posts.
Define and implement auto-generated and auto-graded homework assignments
Maintain and improve existing content
May collaborate with colleagues on the development team to define and develop interactive tools
Collaborate with colleagues in Marketing and Sales to assist with demos, respond to instructor feedback, assist with special requests, and more
May work with project managers to oversee external authoring projects (evaluate project proposals, train external authors to utilize the zyBooks platform, review content to ensure quality and adherence to zyBooks' authoring guidelines)

Python HTML CSS Java Javascript C++Algorithms Content creation Content management Data science Data Structures CI/CD RESTful APIs Data visualization Debugging

Posted about 9 hours ago

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🔥 Principal Data Scientist - Pharma Media

Posted about 9 hours ago

📍 USA

🧭 Full-Time

🔍 Software Development

🏢 Company: Spring & Bond👥 11-50 Digital Marketing Advertising Digital Media Consulting

🔧 Requirements

Master’s degree in data science, Statistics, Mathematics, Computer Science, or related field (PhD preferred)
5+ years of analytics experience
Minimum of 4 years’ hands-on experience in machine learning and relational databases.
Proficient in data manipulation using SQL, Python, and/or similar programming languages.
Solid understanding of media metrics, digital/social analytics, ad technology, and TV ratings.
Strong project-management skills managing cross-functional workflows.
Proven ability to build and maintain client relationships.

💡 Responsibilities

Mentor data scientists, fostering collaboration and professional growth.
Develop and execute a data-science strategy aligned with company objectives.
Design, implement, and optimize predictive models and machine-learning algorithms.
Partner with software engineers, product managers, and business units to deliver client-facing solutions.
Leverage SQL, Python, and R-Shiny to extract insights from large numeric and textual datasets.
Manage model lifecycle: design, training, evaluation, validation, and deployment.
Translate complex analytical results into clear business recommendations and compelling visualizations.
Define and track key performance indicators (KPIs), ensuring data accuracy, integrity, and security.
Analyze digital trends, user behavior, and product performance.
Oversee digital data infrastructure in Snowflake to maintain data health and quality along with Data Engineering team.
Create and maintain technical documentation (system flows, data flows, architecture diagrams) in GitHub repository.
Support measurement strategies, including learning agendas, test plans, and frameworks.
Collaborate regularly with stakeholders to address digital data needs and challenges.
Educate research and business teams on data-best practices and infrastructure.

Python SQL Data Analysis Machine Learning Snowflake Algorithms Data science Data visualization Data modeling

Posted about 9 hours ago

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🔥 Data Scientist – NLP & Real World Evidence (RWE) - Remote

Posted about 12 hours ago

📍 United States, Canada

🔍 Healthcare

🏢 Company: Veradigm👥 5001-10000💰 $100,000,000 Post-IPO Equity almost 10 years agoInformation Services Electronic Health Record (EHR)Hospital Information Technology Health Care

🔧 Requirements

Master’s degree in Data Science, Computer Science, Biomedical Informatics, or a related field.
Proficiency in Python and SQL.
Experience developing ML models, particularly with NLP techniques and libraries (spaCy, Scikit-learn, etc.).
Experience with Azure OpenAI or other large language models.
Familiarity with EMR systems, healthcare data standards (e.g. ICD-10, SNOMED).
Exposure to cloud environments and big data tools (e.g., Snowflake, Azure, Spark).
Demonstrated ability to work with clinical text and health data (e.g., EMRs).

💡 Responsibilities

Design, develop, and deploy NLP and ML models using Python to extract insights from unstructured and semi-structured clinical text.
Leverage Azure OpenAI and other LLM frameworks to enhance clinical data structuring and semantic understanding.
Partner closely with clinical subject matter experts to validate models, ensuring high precision and accuracy in clinical contexts.
Iterate on model development using feedback from real-world applications and clinician review.
Collaborate with Operations teams to design, implement, and optimize an end-to-end data science pipeline from R&D to production.
Ensure data integrity, reproducibility, and compliance with healthcare regulations and best practices.
Work with clients and stakeholders to identify key business problems and expected outcomes.
Explore and assess internal and external data sources to extract relevant features and patterns.
Communicate findings, methodologies, and actionable insights to both technical and non-technical audiences.

Python SQL Cloud Computing Data Analysis ETL Machine Learning Algorithms Azure Data science Data Structures CI/CD RESTful APIs Data visualization

Posted about 12 hours ago

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🔥 Senior Solutions Engineer, West Coast

Posted about 14 hours ago

📍 United States, Canada

🧭 Full-Time

💸 118300.0 - 147800.0 USD per year

🔍 Software Development

🏢 Company: Twilio👥 5001-10000💰 $378,215,525 Post-IPO Equity almost 4 years ago🫂 Last layoff over 1 year agoMessaging SMS Mobile Apps Enterprise Software Software

🔧 Requirements

3+ years of success in a solutions engineering (presales) role with 6+ years of progressive professional experience supporting technical products.
Experience with Data Engineering, Cloud Data Warehouses, Data Modeling, and APIs
Experience with marketing technology such as marketing automation, personalization, journey orchestration, or advertising.

💡 Responsibilities

Partner with Account Executives to execute pre-sales activities including opportunity qualification, discovery, demonstrations, Proof-of-Concept, RFP responses,and justifying business value.
Become an expert builder and evangelist of Segment’s products and partner ecosystem.
Lead technical evaluations with our prospects to uncover their goals and technical pain, in order to design, demonstrate and present innovative solutions that unlock business-level gains.
Develop subject matter expertise on Customer Data Platforms (CDPs) and Segment’s role within the customer data ecosystem.
Act as a trusted advisor to consult with customers and prospects in order to influence their customer data strategy and architecture design.
Build a perspective on customer and market trends by listening to prospects and advocating for customer interests to influence Segment’s strategy and vision.

AWS Cloud Computing ETL Data engineering Data science Communication Skills Problem Solving RESTful APIs Sales experience Marketing Data modeling Scripting Data analytics Data management Customer Success

Posted about 14 hours ago

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🔥 Senior Data Engineer

Posted about 14 hours ago

📍 United States

🧭 Full-Time

💸 145000.0 - 200000.0 USD per year

🔍 Daily Fantasy Sports

🏢 Company: PrizePicks👥 101-250💰 Corporate about 2 years agoGaming Fantasy Sports Sports

🔧 Requirements

5+ years of experience in a data Engineering, or data-oriented software engineering role creating and pushing end-to-end data engineering pipelines.
2+ years of experience acting as technical lead and providing mentorship and feedback to junior engineers.
Extensive experience building and optimizing cloud-based data streaming pipelines and infrastructure.
Extensive experience exposing real-time predictive model outputs to production-grade systems leveraging large-scale distributed data processing and model training.
Experience in most of the following: SQL/NoSQL databases/warehouses: Postgres, BigQuery, BigTable, Materialize, AlloyDB, etc Replication/ELT services: Data Stream, Hevo, etc. Data Transformation services: Spark, Dataproc, etc Scripting languages: SQL, Python, Go. Cloud platform services in GCP and analogous systems: Cloud Storage, Cloud Compute Engine, Cloud Functions, Kubernetes Engine etc. Data Processing and Messaging Systems: Kafka, Pulsar, Flink Code version control: Git Data pipeline and workflow tools: Argo, Airflow, Cloud Composer. Monitoring and Observability platforms: Prometheus, Grafana, ELK stack, Datadog Infrastructure as Code platforms: Terraform, Google Cloud Deployment Manager. Other platform tools such as Redis, FastAPI, and Streamlit.

💡 Responsibilities

Enhance the capabilities of our existing Core Data platforms and develop new integrations with both internal and external APIs within the Data organization.
Work closely with DevOps, architects, and engineers to ensure the success of the Core Data platform.
Collaborate with Analytics Engineers to enhance data transformation processes, streamline CI/CD pipelines, and optimize team collaboration workflows.
Architect and implement Infrastructure as Code (IaC) solutions to automate and streamline the deployment and management of data infrastructure.
Develop and manage CI/CD pipelines to automate and streamline the deployment of data solutions.
Ensure code is thoroughly tested, effectively integrated, and efficiently deployed, in alignment with industry best practices for version control, automation, and quality assurance.
Serve as a Data Engineering thought leader within the broader PrizePicks technology organization by staying current with emerging technologies, implementing innovative solutions, and sharing knowledge and best practices with junior team members and collaborators.
Provide on-call support as part of a shared rotation between the Data and Analytics Engineering teams to maintain system reliability and respond to critical issues.

Leadership PostgreSQL Python SQL Apache Airflow Bash Cloud Computing ETL GCP Git Kafka Kubernetes Data engineering Data science REST API CI/CD RESTful APIs Mentoring Terraform Data modeling

Posted about 14 hours ago

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🔥 Data Scientist - Online Behavioural Analytics & Generative AI

Posted about 15 hours ago

📍 Poland, Estonia, Bulgaria, Serbia, Romania

🔍 Software Development

🏢 Company: Teramind👥 51-100 Productivity Tools Security Cyber Security Enterprise Software Software

🔧 Requirements

5 + years of hands-on experience in Data Science experiments design and working with Generative AI tools and LLMs (e.g. Gemini, OpenAI, Claude, LLama).
Strong statistical analysis skills, including hypothesis testing, regression, clustering, and time-series analysis.
Proficiency in Python, including libraries for data analysis (e.g., Pandas, NumPy), machine learning (e.g., scikit-learn), and data visualization (e.g., Matplotlib, Tableau).
Proven experience in data science, with a focus on online behavioural analytics, user journey analysis, or clickstream data.
Familiarity with Advanced Prompting Strategies, agentic AI frameworks, techniques for retrieval-augmented generation (RAG) and context enrichment using behavioural data.
Experience with Knowledge Graphs, SQL and data extraction from large-scale databases or web logs.
Excellent problem-solving skills and the ability to translate complex data into clear, actionable insights.
Strong communication and collaboration skills for cross-functional teamwork and stakeholder engagement.
Advanced degree (Master’s or Ph.D.) in Computer Science, Statistics, Mathematics, Behavioural Science, or a related field.

💡 Responsibilities

Work closely with AI Engineering and Product teams to collect, clean, and preprocess clickstream data from web and mobile applications, ensuring data quality and consistency.
Design and implement methods to extract behavioural signals from raw click data, including sessionization, event tracking, and feature engineering.
Apply advanced statistical analysis and machine learning techniques to identify user patterns, predict behaviours, and segment audiences.
Conduct exploratory data analysis (EDA) to uncover trends, anomalies, and key behavioural drivers.
Design and evaluate experiments (such as A/B tests) to assess the impact of changes to user interfaces or features on user behaviour.
Collaborate with cross-functional teams (product, UX, marketing) to translate business questions into data-driven analyses and actionable recommendations.
Develop and maintain dashboards and visualizations to communicate findings to both technical and non-technical stakeholders.
Design, build, and evaluate AI workloads utilising Generative AI models using frameworks such as LangChain, Model Context Protocol, and Hugging Face Transformers, with a focus on integrating and augmenting these models with user behavioural data for enhanced context and personalization.
Implement and work with agentic AI frameworks to orchestrate multi-step reasoning and autonomous workflows powered by LLMs, leveraging user clickstream and behavioural data as contextual inputs.
Stay updated with the latest developments in behavioural data science, analytics tools, Generative AI, and agentic AI methodologies.

AWS Docker Python SQL Data Analysis GCP Kubernetes Machine Learning Numpy Tableau Behavioral science Data science Pandas Data visualization A/B testing

Posted about 15 hours ago

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🔥 Data Scientist

Posted about 17 hours ago

📍 United Kingdom

🔍 Advertising

🔧 Requirements

Masters degree or PhD in Computer Science, Statistics, Operations Research, or a related field, with dual degrees a plus.
Have the ability to take an ambiguously defined task, and break it down into actionable steps
Have a comprehensive understanding of statistics, optimization and machine learning
Are proficient in coding, data structures, and algorithms

💡 Responsibilities

Innovate ML algorithms to maximize ROI and advertising performance.
Write production code, sometimes collaborating with Data Engineers, to implement the novel ML algorithms
Prototype potential algorithms and pipelines, test them using historical data, and iterate to modify based on insights

Python Machine Learning Algorithms Data science Data Structures

Posted about 17 hours ago

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🔥 AI Engineer (Associate) - Remote

Posted about 18 hours ago

📍 United States, Canada

💸 100000.0 - 125000.0 USD per year

🏢 Company: huroncareers

🔧 Requirements

Minimum of 4 years of hands-on experience in AI/ML development or intelligent application engineering
Proficiency in Python and familiarity with modern ML/AI libraries (e.g., scikit-learn, PyTorch, TensorFlow, OpenAI APIs)
Experience building APIs or backend services using FastAPI, Flask, or equivalent frameworks
Exposure to agent frameworks (e.g., LangGraph, AutoGen) and vector databases
Familiarity with cloud platforms (Azure, AWS) and containerization tools (Docker)
Familiarity with cloud-based ML platforms such as Azure Machine Learning, AWS SageMaker, or Google AI/ML services
Experience with MLOps pipelines, CI/CD for model delivery, or model monitoring is a plus
Familiarity with orchestration standards or tools such as MCP or agent routing protocols is a plus
Knowledge of AI system evaluation, observability, or prompt performance testing is a plus
Ability to work on cross-functional teams, balance multiple projects, and communicate effectively with technical and non-technical audiences
Cloud certifications in AI/ML services (Azure, AWS, or Google Cloud) is a plus
Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field

💡 Responsibilities

Design and develop AI-powered systems using both traditional ML and generative AI techniques, including prompt engineering, fine-tuning, and embeddings
Build intelligent applications and agents that can perform tasks autonomously or interactively, using frameworks like LangGraph, AutoGen, CrewAI or similar
Create modular, well-documented APIs and service components (e.g., using FastAPI or Flask) to enable model integration and consumption
Develop and manage data pipelines, including data collection, transformation, and quality assurance to support model training
Implement observability and evaluation mechanisms to monitor AI system behavior, including accuracy, drift, reliability, and task-level reasoning
Collaborate with software engineers, data scientists, and solution architects to ensure seamless design, development, and transition to production
Support rapid experimentation as well as robust deployment pipelines, depending on the maturity of each use case
Stay informed on the latest trends in GenAI, AI agents, orchestration protocols, and evaluation frameworks to continuously evolve our capabilities

AWS Backend Development Docker Python Software Development SQL Cloud Computing Data Analysis Flask Frontend Development Kubernetes Machine Learning PyTorch Algorithms API testing Azure Data engineering Data science FastAPI Tensorflow Communication Skills Analytical Skills CI/CD Problem Solving RESTful APIs Adaptability Teamwork JSON Data modeling Data management Debugging

Posted about 18 hours ago

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