CrawlJobs Logo

Data Scientist II (ML Engineering)

clearme.com Logo

Clear

Location Icon

Location:
United States , New York

Category Icon

Job Type Icon

Contract Type:
Not provided

Salary Icon

Salary:

150000.00 - 180000.00 USD / Year

Job Description:

As CLEAR continues to scale, we’re deepening our investment in the data science ecosystem that powers our products, personalization, and decision-making. We’re looking for a Data Scientist to design, develop, and deploy advanced statistical and machine learning models that drive measurable business impact on our digital identity platform. This is a hands-on individual contributor role for someone who blends strong modeling expertise, exceptional Python engineering craft, familiarity with modern ML tooling, and a passion for translating complex data into clear, actionable intelligence. You’ll build and operationalize models that help CLEAR understand, predict, and optimize behavior across our digital identity platform delivering insights and automation that scale.

Job Responsibility:

  • Evolve CLEAR’s predictive modeling ecosystem: design, train, and optimize statistical and machine learning models for our digital identity platform that support product, risk, fraud, operations, and member experience teams
  • Develop high-quality production code including enhancements to feature engineering pipelines, model training workflows, and evaluation frameworks that meet reliability and performance standards
  • Partner with Data Engineering and ML Platform teams to deploy models into production and ensure real-time and batch inference systems run efficiently
  • Advance CLEAR’s AI & ML capabilities by designing reusable modeling components, improving model documentation, and contributing to a roadmap for integrating ML into core products and decision flows
  • Improve experimentation and insight generation by building robust tooling and analytical frameworks, designing statistical tests, and synthesizing results into clear and actionable recommendations for cross-functional teams

Requirements:

  • 3+ years of experience in data science, machine learning, or applied statistics within a modern cloud data environment like AWS Sagemaker
  • Advanced Python with deep experience in scientific libraries (e.g. pandas, NumPy, SciPy, matplotlib), machine learning frameworks (e.g. scikit-learn, XGBoost, LightGBM, pytorch), and model evaluation tooling
  • SQL skills and experience working with cloud data warehouses (e.g. Snowflake, BigQuery, Redshift)
  • Experience with modern ML workflow tools (e.g., Airflow, Dagster, MLflow, Vertex / SageMaker, Voxel 51)
  • Understanding of statistical methods, experiment design, data cleansing, feature engineering, and model interpretability
  • Experience deploying production models and maintaining them through their lifecycle (monitoring, retraining, performance management)
  • Strong communication and storytelling skills
  • A proactive, curious mindset with a passion for standardization, repeatability, and scaling high-quality modeling practices
What we offer:
  • Comprehensive healthcare plans
  • Family-building benefits (fertility and adoption/surrogacy support)
  • Flexible time off
  • Annual wellness stipend
  • Free OneMedical memberships for you and your dependents
  • A CLEAR Plus membership
  • A 401(k) retirement plan with employer match
  • Catered lunches every day
  • Fully stocked kitchens
  • Stipends and reimbursement programs for well-being and learning & development

Additional Information:

Job Posted:
February 17, 2026

Employment Type:
Fulltime
Work Type:
On-site work
Job Link Share:
PREMIUM
More languages and countries
+ Unlock 31694 hidden job offers
Languages
English Čeština Deutsch Ελληνικά Español Français +15
Countries
United States United Kingdom India Canada Australia +
See plans
Plans from $2.99 / month

Looking for more opportunities? Search for other job offers that match your skills and interests.

Briefcase Icon

Similar Jobs for Data Scientist II (ML Engineering)

Engineering Manager II, Data & ML Systems

As an Engineering Manager on the FinTech Data & ML Systems team, you will lead a...
Location
Location
India , Hyderabad
Salary
Salary:
Not provided
uber.com Logo
Uber
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • 10+ years of experience and proven experience as a Software or Data Engineering Manager, leading teams that deliver large-scale data infrastructure or platform solutions
  • Deep technical expertise in distributed data systems, including data ingestion, transformation, storage, and streaming
  • Working knowledge of machine learning workflows and supporting infrastructure (e.g., feature engineering, model training, deployment, and monitoring)
  • Strong leadership, communication, and cross-functional collaboration skills — especially when partnering with analytics, data science, and product teams
  • Demonstrated ability to set vision, define roadmaps, and deliver data-driven solutions that support analytics and ML applications
  • Passion for mentoring engineers and fostering an environment of learning, innovation, and accountability
  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field with 10+ years of experience
Job Responsibility
Job Responsibility
  • Lead a high-performing team of data engineers and platform specialists in designing, implementing, and scaling data and ML solutions that power analytics, decision-making, and automation across FinTech
  • Drive the architecture and delivery of robust data pipelines, feature stores, and data platforms that enable machine learning and advanced analytics use cases
  • Collaborate closely with product managers, data scientists, and ML engineers to define and deliver reliable data and model workflows that support critical FinTech applications
  • Provide technical leadership in data architecture, ETL design, model training pipelines, and productionization of ML workflows
  • Identify opportunities to use data and ML to solve key business challenges, improve efficiency, and unlock new capabilities across payments, compliance, and financial systems
  • Promote a culture of technical excellence, encouraging best practices in system design, testing, observability, and maintainability across both data and ML domains
  • Mentor and develop engineers, fostering a collaborative, inclusive, and high-performance culture where teams can experiment, learn, and grow
  • Ensure reliability and scalability of FinTech data and ML systems through strong engineering discipline and well-defined operational practices
Read More
Arrow Right

AI engineer II

The CNPF Data & AI organisation is looking for an AI Engineer II to support the ...
Location
Location
Ireland , Dublin
Salary
Salary:
Not provided
mastercard.com Logo
Mastercard
Expiration Date
October 10, 2026
Flip Icon
Requirements
Requirements
  • Experience working as an AI engineer, ML engineer, or software engineer on data- or ML-driven systems
  • Working knowledge of Python and common data and ML libraries
  • Basic understanding of how ML models move from development into production
  • Familiarity with data pipelines, APIs, and foundational distributed systems concepts
  • Comfortable working with guidance on ambiguous problems and learning through delivery
  • Strong interest in growing technical depth in AI engineering and ML operations
  • Clear written and verbal communication skills and a collaborative mindset
Job Responsibility
Job Responsibility
  • Build and maintain AI and ML-enabled services under guidance from senior engineers
  • Support deployment and operation of ML models in production environments
  • Participate in data preparation, feature engineering, and experimentation workflows
  • Contribute to ML pipelines, inference services, and batch or real-time data flows
  • Debug, monitor, and improve existing AI systems to ensure reliability and performance
  • Collaborate with data scientists to translate models into working production solutions
  • Follow engineering best practices for testing, documentation, and version control
  • Learn and apply Mastercard standards for security, governance, and responsible AI
  • Fulltime
Read More
Arrow Right

Senior Director of AI Engineering

Coherent Solutions, Incorporated, seeks a Senior Director of AI Engineering in M...
Location
Location
United States , Minneapolis
Salary
Salary:
322000.00 USD / Year
coherentsolutions.com Logo
Coherent Solutions
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Master’s degree in Computer Science, Data Science, Statistics, Computer Engineering, or a closely related technical field
  • at least 10 years of experience in AI, Machine Learning, Data Science, or Advanced Analytics, including at least 5 years in a technical or executive leadership capacity
  • 10 years of: (i) developing, training, and deploying AI and machine learning models using Python, SQL, Spark, and modern statistical and deep-learning frameworks such as Scikit-learn, TensorFlow, or PyTorch
  • and (ii) building predictive modeling systems for enterprise use cases, including propensity models for quality and risks
  • 5 years of: (i) architecting and delivering end-to-end AI platforms and production workflows using Azure, AWS, Databricks, and MLOps tooling such as Spark pipelines, MLflow, and CI/CD automation
  • (ii) applying predictive analytics and/or advanced machine learning techniques (natural language processing and computer vision) to real-world product or enterprise applications
  • (iii) leading teams of Data Scientists, ML Engineers, and AI practitioners within Agile environments
  • and (iv) driving AI strategy and governance, including collaboration with executive stakeholders on ROI modeling, product direction, and roadmap
  • presenting complex AI outcomes to non-technical and C-level audiences, and implementing Responsible AI and data governance frameworks
  • at least 2 years of experience with GenAI/orchestration frameworks, including LangChain or LangGraph
Job Responsibility
Job Responsibility
  • Develop and execute comprehensive go-to-market and engineering strategies for AI, ML, and Generative AI offerings, aligned with corporate objectives set by the CTO
  • Design and oversee scalable AI architectures and MLOps frameworks using Azure ML, AWS Bedrock/SageMaker, Databricks, MLFlow, LangChain/LangGraph
  • Lead the development, validation, and deployment of machine learning and statistical models for prediction, personalization, optimization, and risk detection
  • Apply statistical and causal inference methods - regression, Bayesian inference, and uplift modeling - to measure model performance and business ROI
  • Direct the creation and maintenance of experimentation and analytics platforms supporting continuous testing, ML lifecycle automation, and reproducibility at enterprise scale
  • Oversee development of AI accelerators and reusable components in areas such as NLP, Generative AI, Computer Vision, and Agentic AI
  • Oversee management of data engineering and analytics infrastructure, ensuring data reliability, lineage, and compliance across distributed data pipelines using Python, SQL, and Spark
  • Lead implementation of Responsible AI frameworks, including bias detection, model explainability, and compliance with ethical and regulatory standards (GDPR, SEC/FINRA)
  • Partner with Sales, Marketing, and Delivery teams to define AI-driven value propositions and support client acquisition through technical pre-sales engagement and executive presentations
  • Serve as senior technical advisor to client executives, shaping multi-year AI roadmaps and quantifying business impact
What we offer
What we offer
  • health insurance
  • vision insurance
  • dental insurance
  • life insurance
  • PTO
  • 401k
  • HSA
  • Fulltime
Read More
Arrow Right

Forward-Deployed Data Scientist II

As our customer base continues to grow with the excitement around BrazeAI, we’re...
Location
Location
Romania , Bucharest
Salary
Salary:
Not provided
braze.com Logo
Braze
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor’s degree in Computer Science, Data Science, Mathematics, Engineering, or a related field required
  • Master’s or PhD in a relevant technical discipline preferred
  • 3–5+ years of hands-on experience as a Data Scientist, Machine Learning Engineer, or similar role working with large-scale data and production environments
  • Experience in customer-facing or consulting roles is strongly preferred
  • Proficient in Python (Pandas) and core ML libraries (TensorFlow, Keras, scikit-learn, CatBoost, XGBoost)
  • Skilled in SQL for querying/manipulating datasets, with experience in machine learning pipelines and model deployment
  • You write well-structured, modular, documented code
  • follow strong development practices (Git, CI/CD, testing frameworks, type-hinting, code reviews)
  • and can build scalable, maintainable solutions
Job Responsibility
Job Responsibility
  • Collaborate with customer Analytics/BI teams and Braze colleagues on implementations, including use case definition, data integration, pipeline setup, and ML model configuration
  • Extend product capabilities by improving architecture and developing reusable data pipelines, APIs, and components
  • Work closely with the RL pipeline development team to refine and advance our reinforcement learning (self-learning) algorithms
  • Contribute to shaping BrazeAI product strategy and roadmap through customer-facing insights and technical expertise
  • Provide ongoing technical expertise to ensure successful adoption, measurable outcomes, and long-term customer success
What we offer
What we offer
  • Competitive compensation that may include equity
  • Retirement and Employee Stock Purchase Plans
  • Flexible paid time off
  • Comprehensive benefit plans covering medical, dental, vision, life, and disability
  • Family services that include fertility benefits and equal paid parental leave
  • Professional development supported by formal career pathing, learning platforms, and a yearly learning stipend
  • A curated in-office employee experience, designed to foster community, team connections, and innovation
  • Opportunities to give back to your community, including an annual company-wide Volunteer Week and donation matching
  • Employee Resource Groups that provide supportive communities within Braze
Read More
Arrow Right

Artificial Intelligence Data Engineer II

The Artificial Intelligence Data Engineer II designs, develops, and manages scal...
Location
Location
United States , Los Angeles
Salary
Salary:
105267.00 - 173689.00 USD / Year
lacare.org Logo
L.A. Care Health Plan
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's Degree in Computer Science or Related Field
  • At least 5 years of experience in data engineering
  • At least 2 years of experience focused on AI/ML data pipelines
  • Hands on experience working on GenAI projects (chatbot implementations, Natural Language Processing (NLP), Sentiment Analysis, recommendation systems, anomaly detection etc.
  • Proficient skills in Python, SQL, Spark, AWS (Glue, S3, Lambda), Snowflake (Snowpark Container Services), IDMC, prompt engineering, model inference and fine-tuning, RAG and working with MCP, Vector databases
  • Proficient technical and data engineering skills
  • Solid understanding of supervised and unsupervised machine learning methods, feature engineering, model evaluation, and validation techniques
  • Ability to operationalize models in production environments, including basic MLOps practices (version control, CI/CD, reproducibility)
  • Ability to communicate complex AI/ML concepts effectively to non-technical stakeholders
  • Excellent documentation skills, ensuring reproducibility, clarity of assumptions, and transparency of model design
Job Responsibility
Job Responsibility
  • Design and implement scalable data pipelines for AI/ML workloads
  • Develop and deploy AI/ML solutions using Python, Snowpark, or cloud-native ML services
  • Build and manage feature stores to support model training and inference
  • Integrate structured and unstructured data sources from internal and external systems
  • Collaborate with data scientists to understand data requirements and optimize pipelines
  • Implement data quality checks, metadata tagging, and lineage tracking
  • Ensure compliance with Health Insurance Portability and Accountability Act (HIPAA), Centers for Medicare and Medicaid Services (CMS), and enterprise data governance standards
  • Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and Informatica Data Management Cloud (IDMC)
  • Implement DevOps/MLOps and Continuous Integration (CI)/Continuous Delivery (CD) pipelines using git actions or similar tools
  • Monitor pipeline performance and troubleshoot issues in production environments
What we offer
What we offer
  • Paid Time Off (PTO)
  • Tuition Reimbursement
  • Retirement Plans
  • Medical, Dental and Vision
  • Wellness Program
  • Volunteer Time Off (VTO)
  • Fulltime
Read More
Arrow Right

Artificial Intelligence Data Engineer II

The Artificial Intelligence Data Engineer II designs, develops, and manages scal...
Location
Location
United States , Los Angeles
Salary
Salary:
105267.00 - 173689.00 USD / Year
lacare.org Logo
L.A. Care Health Plan
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Bachelor's Degree in Computer Science or Related Field
  • At least 5 years of experience in data engineering
  • At least 2 years of experience focused on AI/ML data pipelines
  • Hands on experience working on GenAI projects (chatbot implementations, Natural Language Processing (NLP), Sentiment Analysis, recommendation systems, anomaly detection etc.
  • Proficient skills in Python, SQL, Spark, AWS (Glue, S3, Lambda), Snowflake (Snowpark Container Services), IDMC, prompt engineering, model inference and fine-tuning, RAG and working with MCP, Vector databases
  • Proficient technical and data engineering skills
  • Solid understanding of supervised and unsupervised machine learning methods, feature engineering, model evaluation, and validation techniques
  • Ability to operationalize models in production environments, including basic MLOps practices (version control, CI/CD, reproducibility)
  • Ability to communicate complex AI/ML concepts effectively to non-technical stakeholders
  • Excellent documentation skills, ensuring reproducibility, clarity of assumptions, and transparency of model design
Job Responsibility
Job Responsibility
  • Design and implement scalable data pipelines for AI/ML workloads
  • Develop and deploy AI/ML solutions using Python, Snowpark, or cloud-native ML services
  • Build and manage feature stores to support model training and inference
  • Integrate structured and unstructured data sources from internal and external systems
  • Collaborate with data scientists to understand data requirements and optimize pipelines
  • Implement data quality checks, metadata tagging, and lineage tracking
  • Ensure compliance with Health Insurance Portability and Accountability Act (HIPAA), Centers for Medicare and Medicaid Services (CMS), and enterprise data governance standards
  • Automate data ingestion and transformation using tools like AWS Glue, Snowflake, and Informatica Data Management Cloud (IDMC)
  • Implement DevOps/MLOps and Continuous Integration (CI)/Continuous Delivery (CD) pipelines using git actions or similar tools
  • Monitor pipeline performance and troubleshoot issues in production environments
What we offer
What we offer
  • Paid Time Off (PTO)
  • Tuition Reimbursement
  • Retirement Plans
  • Medical, Dental and Vision
  • Wellness Program
  • Volunteer Time Off (VTO)
  • Fulltime
Read More
Arrow Right

Data Scientist II

The Copilot and Platform Ecosystem (CAPE) team at Microsoft is on a mission to d...
Location
Location
United States , Redmond
Salary
Salary:
100600.00 - 199000.00 USD / Year
https://www.microsoft.com/ Logo
Microsoft Corporation
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field
  • OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) or consulting experience
  • OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 2+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
  • OR equivalent experience
  • Ability to meet Microsoft, customer and/or government security screening requirements
  • This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Job Responsibility
Job Responsibility
  • Partner with data engineering, product management, and engineering to define analytical questions, success metrics, and hypotheses that drive Copilot business outcomes
  • Analyze large-scale product and customer telemetry (e.g., Kusto/ADX, Cosmos, logs, usage signals) to deliver clear, actionable insights for leaders and partner teams
  • Design and interpret experiments and evaluations (A/B tests, cohort/retention analysis, causal methods as appropriate) to measure impact of features, agents, and platform changes
  • Own and evolve core metrics and definitions (engagement, retention, adoption, quality), ensuring consistency and trust across reporting and dashboards
  • Improve data quality, freshness, and correctness by identifying gaps/anomalies and strengthening signal pipelines in partnership with data engineering
  • Build analytical models or lightweight ML to support forecasting, segmentation, classification, and outcome measurement as needed
  • Communicate complex analyses as concise narratives for technical and non-technical audiences
  • contribute to documentation and analytics best practices across CAPE
  • Fulltime
Read More
Arrow Right

Data Scientist

We are seeking a versatile and proactive Data Scientist to join our dynamic team...
Location
Location
India , Pune
Salary
Salary:
Not provided
Jash Data Sciences
Expiration Date
Until further notice
Flip Icon
Requirements
Requirements
  • Strong Python programming skills with hands-on project experience
  • Expertise in Machine Learning and Deep Learning algorithms (Random Forests, GBMs, Neural Networks, CNNs, RNNs, Transformers, Ensemble methods)
  • Proficiency in TensorFlow or PyTorch, along with scikit-learn and pandas
  • Familiarity with modern ML techniques: Transfer Learning, Few-shot Learning, Self-supervised Learning
  • Experience with NLP, Computer Vision, or Time Series Analysis
  • Hands-on experience with LLM providers (OpenAI, Anthropic Claude, Google Gemini, or open-source models)
  • Proficiency with GenAI orchestration frameworks (LangChain, LangGraph, LlamaIndex, or DSPy)
  • Experience building RAG applications with vector databases (Pinecone, Weaviate, Chroma, FAISS)
  • Strong prompt engineering skills and understanding of prompt optimization techniques
  • Knowledge of fine-tuning techniques (LoRA, QLoRA) and when to apply them
Job Responsibility
Job Responsibility
  • Deliver end-to-end data science projects by applying Machine Learning and Deep Learning fundamentals to solve complex problems
  • Derive actionable insights for a variety of problems, industries, and domains using statistical analysis and advanced data science techniques
  • Develop high-quality software solutions with Python and other programming languages. Collaborate with developers to understand and improve existing code or create new solutions
  • Build and deploy production-ready LLM applications using modern frameworks and best practices
  • Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases and embedding models
  • Perform prompt engineering and optimization to maximize LLM performance for specific use cases
  • Implement agentic AI systems and multi-agent workflows for complex automation tasks
  • Evaluate and benchmark LLM outputs using appropriate metrics and testing frameworks
  • Build sophisticated data pipelines for large-scale data processing using modern orchestration tools
  • Optimize database performance and create efficient SQL queries
What we offer
What we offer
  • Competitive salary commensurate with experience
  • Opportunity to work on diverse, cutting-edge AI/ML projects
  • Collaborative and innovation-driven work environment
  • Rapid growth and continuous learning opportunities
  • Exposure to latest AI technologies and industry best practices
Read More
Arrow Right