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🔥 Director | Data Science
Posted about 1 hour ago

📍 United States

🧭 Full-Time

🔍 Healthcare

🏢 Company: Machinify👥 51-100💰 $10,000,000 Series A over 6 years agoArtificial Intelligence (AI)Business IntelligencePredictive AnalyticsSaaSMachine LearningAnalytics

  • 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
  • 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.

AWSLeadershipPythonSQLApache AirflowCloud ComputingData AnalysisETLKerasMachine LearningMLFlowNumpyPeople ManagementCross-functional Team LeadershipAlgorithmsData engineeringData scienceData StructuresPandasSparkTensorflowCommunication SkillsProblem SolvingAgile methodologiesRESTful APIsMentoringData visualizationTeam managementStrategic thinkingData modeling

Posted about 1 hour ago
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🔥 iAgami - Python Fullstack Developer
Posted about 15 hours ago

📍 Pan India, IN

🧭 Full-Time

🔍 Software Development

🏢 Company: Nexthire

  • Minimum 4 years of hands-on experience in full stack development.
  • Strong proficiency in Python, particularly Django and Pandas.
  • Solid experience with React for front-end development.
  • Excellent communication and interpersonal skills.
  • Ability to work independently and manage tasks in a remote environment.
  • Educational Qualification: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.
  • Design, develop, and maintain web applications using Python (Django, Pandas) and React.
  • Collaborate with cross-functional teams to define, design, and ship new features.
  • Write clean, scalable, and efficient code.
  • Debug and troubleshoot software issues in a timely manner.
  • Participate in code reviews and maintain coding standards.
  • Communicate effectively with team members and stakeholders.

PythonSQLDjangoFull Stack DevelopmentPandasReactRESTful APIs

Posted about 15 hours ago
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🔥 Staff, Machine Learning Engineer
Posted about 17 hours 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 agoMessagingSMSMobile AppsEnterprise SoftwareSoftware

  • 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
  • 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.

AWSPythonSQLKerasMachine LearningMySQLNumpyAirflowData sciencePandas

Posted about 17 hours ago
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🔥 Data Scientist - Online Behavioural Analytics & Generative AI
Posted 1 day ago

📍 Poland, Estonia, Bulgaria, Serbia, Romania

🔍 Software Development

🏢 Company: Teramind👥 51-100Productivity ToolsSecurityCyber SecurityEnterprise SoftwareSoftware

  • 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.
  • 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.

AWSDockerPythonSQLData AnalysisGCPKubernetesMachine LearningNumpyTableauBehavioral scienceData sciencePandasData visualizationA/B testing

Posted 1 day ago
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🔥 Principal AI/SOTIF Safety Engineer Technical Lead
Posted 2 days ago

📍 United States

🧭 Full-Time

💸 193600.0 - 296600.0 USD per year

🔍 Software Development

🏢 Company: careers_gm

  • 7+ years of experience in machine learning, engineering, data science, or a related field of expertise
  • ISO 8800, ISO 24118 and other applicable industry standards and best practices for autonomous vehicles, aerospace and/or robotics.
  • Setting the strategy for E2E validation using techniques appropriate to validate AI models
  • Python, R, Java, PySpark, PyTorch, TensorFlow, Scikit-learn, LangChain, SQL
  • Large Language Models (LLMs), Generative AI, RAG, Deep learning, Reinforcement Learning, Natural Language Processing (NLP), SVM, XGBoost, Random Forest, Decision Trees, Clustering
  • Microsoft Azure (Data Lake, Machine Learning, Databricks)
  • MLflow, Model Monitoring & Versioning, Docker & Kubernetes, GitHub, Jira
  • Tableau, PowerBI, Pandas, NumPy
  • Proven track record providing technical safety leadership in AI/ML and AV development
  • Referencing ISO 8800, ISO 24118 and AV industry best practices, develop the strategy for ensuring safe AI/ML and autonomous system development, deployment and maintenance.
  • Work with software, data science and systems engineering teams to ensure GM safely trains new machine learning models to solve complex business problems.
  • Ensure continuity of safety as we enhance existing machine learning models to increase performance and adapt to our changing business landscape.
  • Set the safety standard for how we prototype, test and deploy new AI solutions, including Generative AI, to solve business problems.
  • Set the strategy for testing and validation of data sets and develop an assurance plan.
  • Set the strategy for how we systematically break down operational design domain components and driving behavior components and how these are validated in aggregate and on a per behavior level.
  • Work with data science, systems engineering and software teams to set the strategy for how we establish safety launch targets across vehicle behaviors and in aggregate
  • Setup an assurance process to validate launch targets have been achieved

DockerLeadershipPythonSQLArtificial IntelligenceCloud ComputingData AnalysisJavaJava EEKubernetesMachine LearningMicrosoft AzureMLFlowNumpyPyTorchJiraTableauAlgorithmsData sciencePandasTensorflowCommunication SkillsAnalytical SkillsCollaborationAgile methodologiesRESTful APIsOrganizational skillsWritten communicationProblem-solving skillsTeamworkRisk ManagementData visualizationStrategic thinkingData modelingDebugging

Posted 2 days ago
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🔥 Senior Data Scientist, US
Posted 2 days ago

📍 Texas, Denver, CO

💸 148000.0 - 189000.0 USD per year

🔍 SaaS

🏢 Company: Branch Metrics

  • 4+ years of relevant experience in data science, analytics, or related fields.
  • Degree in Statistics, Mathematics, Computer Science, or related field.
  • Proficiency with Python, SQL, Spark, Bazel, CLI (Bash/Zsh).
  • Expertise in Spark, Presto, Airflow, Docker, Kafka, Jupyter.
  • Strong knowledge of ML frameworks (scikit-learn, pandas, xgboost, lightgbm).
  • Experience deploying models to production on AWS infrastructure and experience with the basic AWS services.
  • Advanced statistical knowledge (regression, A/B testing, Multi-Armed Bandits, time-series anomaly detection).
  • Collaborate with stakeholders to identify data-driven business opportunities.
  • Perform data mining, analytics, and predictive modeling to optimize business outcomes.
  • Conduct extensive research and evaluate innovative approaches for new product initiatives.
  • Develop, deploy, and monitor custom models and algorithms.
  • Deliver end-to-end production-ready solutions through close collaboration with engineering and product teams.
  • Identify opportunities to measure and monitor key performance metrics, assessing the effectiveness of existing ML-based products.
  • Serve as a cross-functional advisor, proposing innovative solutions and guiding product and engineering teams toward the best approaches.
  • Anticipate and clearly articulate potential risks in ML-driven products.
  • Effectively integrate solutions into existing engineering infrastructure.

AWSDockerPythonSQLBashKafkaMachine LearningAirflowRegression testingPandasSparkRESTful APIsTime ManagementA/B testing

Posted 2 days ago
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🔥 Sr Data Scientist
Posted 3 days ago

📍 United States

🧭 Full-Time

💸 211536.0 - 287100.0 USD per year

🔍 Software Development

🏢 Company: jobs

  • SQL and Python programming to query and validate the accuracy of datasets
  • Design and develop workflow orchestration tools
  • Python scripting to develop statistical and machine learning models for classification
  • Use agile software development principle to design, plan and structure deployment of software products
  • Develop machine learning models to segment customer behavior, identify market concentration and volatility using Python and Spark ML
  • Building KPIs (Key Performance Indicators) and metrics, validating using statistical hypothesis testing
  • Expertise in Cloud Computing resources and maintaining data on cloud storage
  • Big Data processing for data cleaning
  • Deploy self-serving data visualization tools, automating, generating reports and consolidating visually on tableau dashboards
  • Develop data engineering pipelines and transformations
  • Lead, build and implement analytics functions for Honey features
  • Conduct impactful data analysis to improve customer experiences and inform product development
  • Collaborate cross-functional support teams to build world-class products and design hypothesis-driven experiments
  • Gather and collate business performance and metrics to recommend improvements, automation, and data science directives for overall business performance
  • Present findings and recommendations to senior level/non-technical stakeholders
  • Maintain large datasets by performing batch scheduling and pipelining ETL operations
  • Perform ad-hoc exploratory analysis on datasets to generate insights and automate production ready solutions
  • Develop machine learning-based models to improve forecasting and predictive analytics
  • Implement innovative quantitative analyses, test new data wrangling techniques, and experiment with new visualization tools to deliver scalable analytics
  • Develop and create programming paradigms and utilizing tools like git, data structures, OOP, and network algorithms

PythonSQLCloud ComputingData AnalysisETLGitMachine LearningNumpyTableauAlgorithmsData engineeringData StructuresPandasSparkTensorflowAgile methodologiesData visualizationData modeling

Posted 3 days ago
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🔥 (1070) Senior AI Python Engineer
Posted 3 days ago

📍 LATAM

🧭 Full-Time

🔍 Software Development

🏢 Company: Nearsure👥 501-1000Staffing AgencyOutsourcingSoftware

  • 5+ Years of experience working with the Python programming language, with the ability to work across AI, infrastructure, and tooling codebases.
  • 3+ Years of experience working in cloud environments (AWS or GCP).
  • 2+ Years of experience working with scripting languages (e.g., Bash, Go).
  • 1+ Years of experience working with containerization (Docker) and orchestration (Kubernetes), and with CI/CD systems and infrastructure automation tools (e.g., Terraform, Ansible).
  • 1+ Years of practical, hands-on experience with code-generation tools such as Codex, StarCoder, Claude, or GPT family.
  • Solid understanding of the full Software Development Lifecycle (planning, coding, testing, releasing, monitoring).
  • Practical, hands-on experience with large language models (LLMs).
  • Experience prototyping, benchmarking, and deploying AI solutions to improve developer workflows.
  • Strong understanding of software development automation and developer productivity enhancement techniques.
  • Familiarity with prompt engineering and retrieval-augmented generation (RAG) pipelines.
  • Ability to explain complex AI solutions and technical concepts to cross-functional and non-technical teams.
  • Research-driven mindset with curiosity for testing new AI ideas, tools, and approaches.
  • Strong problem-solving skills focused on identifying inefficiencies and applying AI to increase delivery velocity.
  • Advanced English Level is required for this role as you will work with US clients. Effective communication in English is essential to deliver the best solutions to our clients and expand your horizons.
  • Build AI-powered tools to enhance each stage of the SDLC: from code generation and code reviews to testing, documentation, and deployment.
  • Develop internal assistants and copilots to reduce cognitive load and empower developers to move faster with fewer manual steps.
  • Automate repetitive development and operational tasks (e.g., writing IaC, generating release notes, updating documentation).
  • Investigate GenAI solutions (e.g., GitHub Copilot, CodeLlama, GPT-Engineer) to improve CI/CD workflows and eliminate friction in delivery pipelines.
  • Design, benchmark, and deploy AI-driven solutions that reduce lead time, increase deployment frequency, and enhance reliability.
  • Explore custom model fine-tuning and retrieval-augmented generation (RAG) approaches when needed.
  • Prototype features like AI-driven deployment optimizations, cost-aware autoscaling, or predictive incident resolution.
  • Embed AI into DevOps processes to identify bottlenecks, automate root cause analysis, and surface continuous delivery insights.
  • Collaborate with SRE and developer experience teams to evolve our Internal Developer Platform (IDP) with intelligent automation.
  • Partner with engineering, DevOps, and product teams to identify key pain points and deliver impactful AI interventions.
  • Share findings through workshops, whitepapers, and internal demos to scale learnings across the organization.

AWSBackend DevelopmentDockerPythonSoftware DevelopmentArtificial IntelligenceBashCloud ComputingData AnalysisFlaskFrontend DevelopmentFull Stack DevelopmentGCPKubernetesMachine LearningNumpyAlgorithmsAPI testingData StructuresFastAPIGoWebRTCPandasTensorflowCI/CDRESTful APIsDevOpsTerraformJSONAnsibleSoftware EngineeringDebugging

Posted 3 days ago
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🔥 Bioinformatics Engineer 1, Custom Data Report (Temp - 6 months)
Posted 3 days ago

📍 USA

🧭 Temporary

🔍 Bioinformatics

🏢 Company: Personalis, Inc

  • Expertise in Python, particularly in using pandas data frames for data wrangling.
  • Familiarity with standard bioinformatics NGS data formats and annotations.
  • Proficiency in Unix/Linux environments and Bash scripting.
  • Understanding of different assays and modes of sequencing (WGS vs. Exome, RNA-seq, Tumor vs. Normal, Somatic vs. Germline, etc.).
  • Understanding of NGS biomarkers related to cancer (e.g. copy numbers, fusions, SNV and INDELs).
  • Work with our existing frameworks to execute custom report generation.
  • Work within a team scrum context to ensure timely delivery across multiple concurrent projects.
  • Perform detailed QC of the generated reports to ensure all of the content meets the customers' specifications prior to delivery.
  • Using established QC tools for systematically testing the accuracy of generated custom reports to detect hidden errors and irregularities in the data.
  • Collaborate with and provide feedback to the Custom Data Report (CDR) team to drive continuous improvement.

PythonSQLBashGitJiraPandasConfluence

Posted 3 days ago
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🔥 Lead Software Engineer - AI Data Systems
Posted 4 days ago

📍 21 U.S. states

🧭 Full-Time

💸 151500.0 - 215500.0 USD per year

🔍 Software Development

🏢 Company: Upwork👥 501-1000💰 over 8 years ago🫂 Last layoff about 2 years agoMarketplaceFreelanceCopywritingPeer to Peer

  • Strong software engineering background with deep experience in building data collection, transformation, and featurization pipelines at scale.
  • Proficiency in Python, including async programming and concurrency tools, as well as data-centric frameworks such as Pandas, Spark, or Apache Beam.
  • Familiarity with ML model development workflows and infrastructure, including dataset versioning, experiment tracking, and model evaluation.
  • Experience deploying and scaling AI systems in cloud environments such as AWS, GCP, or Azure.
  • Proven success operating in highly ambiguous environments such as research labs, startups, or fast-paced product teams.
  • A track record of working with or alongside high-caliber peers in top engineering teams, research groups, or startup ecosystems.
  • Growth mindset, strong communication skills, and a commitment to inclusive collaboration and continuous learning.
  • Design and implement systems to collect and curate high-quality training datasets for supervised, unsupervised, and reinforcement learning use cases.
  • Build scalable featurization and preprocessing pipelines to transform raw data into structured inputs for AI/ML model development.
  • Partner with ML engineers and researchers to define data requirements and production workflows that support LLM-based agents and autonomous AI systems.
  • Lead the development of infrastructure that enables experimentation, evaluation, and deployment of machine learning models in production environments.
  • Support orchestration and real-time inference pipelines using Python and modern cloud-native tools, ensuring low-latency and high availability.
  • Mentor engineers and foster a high-performance, collaborative engineering culture grounded in technical excellence and curiosity.
  • Drive cross-functional alignment with product, infrastructure, and research stakeholders, ensuring clarity on progress, goals, and architecture.

AWSDockerLeadershipPythonSQLApache AirflowCloud ComputingGitKubernetesMachine LearningAlgorithmsData engineeringData scienceData StructuresREST APIPandasSparkCommunication SkillsCI/CDMentoringTeamworkSoftware Engineering

Posted 4 days ago
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