Full-Stack Developer Jobs

Data science

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🔥 Senior Writer, AI

Posted about 7 hours ago

📍 United States

💸 120000.0 - 150000.0 USD per year

🔍 Journalism

🏢 Company: Forbes👥 251-500💰 almost 25 years agoInformation Services Publishing News

🔧 Requirements

Bachelor’s degree with 5+ years of journalism experience
Strong writer who communicates effectively and clearly with a strong point of view that stands out
Well sourced in the AI community with a proven track record for turning tips into stories
Versed in the technical side of AI, as well as the finance of startup fundraising, and able to hold their own with researchers and investors alike
Team player and happy collaborator who is willing to crash out a quick hit, dive into an investigation and go in-depth for a print profile, as need requires
Overflowing with story ideas drawn from sourcing, sharp observation and on-the-ground reporting
Comfortable working remotely

💡 Responsibilities

Pitch, report and write must-read stories about artificial intelligence companies and entrepreneurs
Regularly break news, including exclusives, funding scoops and investigations
Conceive and report features for the website and magazine, including pitching profiles and cover stories
Participate in the reporting of AI 50 and contribute to other Forbes lists
Represent Forbes at live events and conferences
Participate in Forbes videos related to reporting

Artificial Intelligence Data Analysis Data Mining Machine Learning Data science Research Reporting Writing Finance

Posted about 7 hours ago

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🔥 Director | Data Science

Posted about 11 hours ago

📍 United States

🧭 Full-Time

🔍 Healthcare

🏢 Company: Machinify👥 51-100💰 $10,000,000 Series A over 6 years agoArtificial Intelligence (AI)Business Intelligence Predictive Analytics SaaS Machine Learning Analytics

🔧 Requirements

10+ years of data science experience, with at least 5 years in a leadership role, including a leadership role at a start-up. Proven track record of managing data teams and delivering complex, high-impact products from concept to deployment
Strong knowledge of data privacy regulations and best practices in data security
Exceptional team management abilities, with experience in building and leading high-performing teams
Ability to think strategically and execute methodically
Ability to drive change and inspire a distributed team
Strong problem-solving skills and a data-driven mindset
Ability to communicate effectively, collaborating with diverse groups to solve complex problems

💡 Responsibilities

Provide direction and guidance to a team of Senior and Staff Data Scientists, enabling them to do their best work
Collaborate with the leadership team to define key technical and business metrics and objectives
Translate objectives into internal team priorities and assignments
Drive sprints and work with cross-functional stakeholders to appropriately prioritize various initiatives to improve customer metrics
Hire, mentor and develop team members
Foster a culture of innovation, collaboration, and continuous improvement
Communicate technical concepts and strategies to technical and non-technical stakeholders effectively
Own the success of various models on the field by continuously monitoring KPI’s and initiating projects to improve quality.

AWS Leadership Python SQL Apache Airflow Cloud Computing Data Analysis ETL Keras Machine Learning MLFlow Numpy People Management Cross-functional Team Leadership Algorithms Data engineering Data science Data Structures Pandas Spark Tensorflow Communication Skills Problem Solving Agile methodologies RESTful APIs Mentoring Data visualization Team management Strategic thinking Data modeling

Posted about 11 hours ago

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🔥 Staff, Machine Learning Engineer

Posted 1 day ago

📍 Canada

🧭 Full-Time

💸 172800.0 - 216000.0 CAD 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

5+ years of applied ML engineering experience
Develop and Deploy AI Models: Build and deploy machine learning models leveraging NLP techniques and GenAI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base.
Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes.
Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sagemaker, Lambda, S3, Kendra), MySQL, Airtable, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions.
Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zendesk to inform model development and enhance predictive accuracy.
Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative GenAI use cases and solutions

💡 Responsibilities

Develop and Deploy AI/ML Models: Build and deploy machine learning models by leveraging NLP, recommendation systems & Gen AI-powered applications, to production environments, ensuring they meet the diverse needs of Twilio's verticals and customer base.
Collaborate Across Teams: Work closely with product, program, analytics, and engineering teams to implement and refine machine learning, statistical, and forecasting models that drive business outcomes.
Utilize Advanced Technical Stack: Leverage our technical stack, including Python, SQL, R, AWS (Sage maker, Lambda, S3, Kendra), MySQL, Air table, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Keras, to develop robust and scalable AI/ML solutions.
Integrate Enterprise Data Sources: Effectively utilize enterprise data sources like Salesforce and Zen desk to inform model development and enhance predictive accuracy.
Harness the Power of LLMs: Apply knowledge of Large Language Models (LLMs) such as OpenAI's GPT models, Claude, Gemini, Llama, Whisper, and Groq to develop innovative Gen AI use cases and solutions.

AWS Python SQL Keras Machine Learning MySQL Numpy Airflow Data science Pandas

Posted 1 day ago

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🔥 Senior Writer, AI

Posted 1 day ago

📍 United States

💸 120000.0 - 150000.0 USD per year

🔍 Journalism

🔧 Requirements

Bachelor’s degree with 5+ years of journalism experience
Strong writer who communicates effectively and clearly with a strong point of view that stands out
Well sourced in the AI community with a proven track record for turning tips into stories
Versed in the technical side of AI, as well as the finance of startup fundraising, and able to hold their own with researchers and investors alike
Team player and happy collaborator who is willing to crash out a quick hit, dive into an investigation and go in-depth for a print profile, as need requires
Overflowing with story ideas drawn from sourcing, sharp observation and on-the-ground reporting
Comfortable working remotely

💡 Responsibilities

Pitch, report and write must-read stories about artificial intelligence companies and entrepreneurs
Regularly break news, including exclusives, funding scoops and investigations
Conceive and report features for the website and magazine, including pitching profiles and cover stories
Participate in the reporting of AI 50 and contribute to other Forbes lists
Represent Forbes at live events and conferences
Participate in Forbes videos related to reporting

Artificial Intelligence Data Analysis Machine Learning Data science Research Writing Finance

Posted 1 day ago

Apply

🔥 Staff Product Manager, Benefits Platform

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 215900.0 - 254000.0 USD per year

🔍 Healthcare

🔧 Requirements

You have 6+ years building platforms that leverage ML for automated decision-making, preferably in healthcare, insurance, or adjacent risk domains.
You understand the complexities of health insurance - from claims processing to benefits determination - and have built systems that improve billing accuracy or clean claims rates.
You're comfortable diving deep with engineering and data science teams on complex technical problems and can drive architectural decisions for scalable platforms.
You've led initiatives requiring difficult tradeoffs between accuracy, speed, and user experience, and can influence stakeholders across multiple teams.
You excel at analyzing complex datasets to identify root causes and drive systematic improvements to platform performance.

💡 Responsibilities

Own the benefits determination platform strategy and roadmap to achieve company goals for billing accuracy and collections loss reduction.
Build ML-powered systems that interpret complex insurance data and handle thousands of payer-specific edge cases.
Drive technical decisions on platform architecture, model deployment, and system scalability with engineering leadership.
Collaborate with Engineering and Data Science on developing models that improve benefits interpretation accuracy and confidence scoring.
Partner with Insurance Operations and Customer Care to understand manual intervention patterns and automate high-volume workflows.

SQL Data Analysis Machine Learning Product Management Cross-functional Team Leadership Data science RESTful APIs Data modeling

Posted 1 day ago

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🔥 Lead Machine Learning Infrastructure Engineer - Infrastructure & Data

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 185500.0 - 293750.0 USD per year

🔍 Software Development

🔧 Requirements

Strong technical expertise in designing and building scalable ML infrastructure.
Experience with distributed systems and cloud-based ML platforms.
Proficiency in programming languages such as Python, Java, or Scala.
Deep understanding of ML workflows, including data pipelines, model training, and deployment.
Passion for innovation and eagerness to implement the latest advancements in ML infrastructure.
Strong problem-solving skills and ability to optimize complex systems for performance and reliability.
Collaborative mindset with excellent communication skills to work across teams.
Ability to thrive in a fast-paced, dynamic environment with evolving technical challenges.

💡 Responsibilities

Design, implement, and optimize distributed systems and infrastructure components to support large-scale machine learning workflows, including data ingestion, feature engineering, model training, and serving.
Develop and maintain frameworks, libraries, and tools that streamline the end-to-end machine learning lifecycle, from data preparation and experimentation to model deployment and monitoring.
Architect and implement highly available, fault-tolerant, and secure systems that meet the performance and scalability requirements of production machine learning workloads.
Collaborate with machine learning researchers and data scientists to understand their requirements and translate them into scalable and efficient software solutions.
Stay current with advancements in machine learning infrastructure, distributed computing, and cloud technologies, integrating them into our platform to drive innovation.
Mentor junior engineers, conduct code reviews, and uphold engineering best practices to ensure the delivery of high-quality software solutions.

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

Posted 1 day ago

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🔥 Staff Product Manager, Benefits Platform

Posted 1 day ago

📍 United States

🧭 Full-Time

💸 215900.0 - 254000.0 USD per year

🔍 Healthcare

🏢 Company: Headway👥 201-500💰 $125,000,000 Series C over 1 year agoMental Health Care

🔧 Requirements

6+ years building platforms that leverage ML for automated decision-making, preferably in healthcare, insurance, or adjacent risk domains.
Understand the complexities of health insurance - from claims processing to benefits determination - and have built systems that improve billing accuracy or clean claims rates.
Comfortable diving deep with engineering and data science teams on complex technical problems and can drive architectural decisions for scalable platforms.
Led initiatives requiring difficult tradeoffs between accuracy, speed, and user experience, and can influence stakeholders across multiple teams.
Excel at analyzing complex datasets to identify root causes and drive systematic improvements to platform performance.

💡 Responsibilities

Own the benefits determination platform strategy and roadmap to achieve company goals for billing accuracy and collections loss reduction.
Build ML-powered systems that interpret complex insurance data and handle thousands of payer-specific edge cases.
Drive technical decisions on platform architecture, model deployment, and system scalability with engineering leadership.
Collaborate with Engineering and Data Science on developing models that improve benefits interpretation accuracy and confidence scoring.
Partner with Insurance Operations and Customer Care to understand manual intervention patterns and automate high-volume workflows.

AWS Backend Development Leadership SQL Data Analysis Machine Learning Product Management Product Operations Cross-functional Team Leadership Product Development Strategy Data science Communication Skills Analytical Skills RESTful APIs Data modeling

Posted 1 day ago

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

Posted 2 days 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 2 days ago

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🔥 IT Content Author

Posted 2 days 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 2 days ago

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🔥 Principal Data Scientist - Pharma Media

Posted 2 days 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 2 days ago

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