Senior Data Scientist

phData

Senior Data Scientist building machine learning and Generative AI solutions for large enterprises at phData, a remote-first data and AI consultancy. Designing production-ready models, pipelines, and MLOps systems.

Posted 8/5/2026full-timeRemote • 🇺🇸 United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and deploying machine learning and Generative AI solutions, with a strong foundation in advanced mathematics, statistics, and computer science principles. Proficient in collaborating with cross-functional teams and implementing MLOps practices to ensure model performance and scalability.

Highest-signal resume keywords

Machine Learning Model DevelopmentDeep Learning ExpertisePython and SQL MasteryMLOps ImplementationCloud Development on AWS or Azure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language ProcessingComputer VisionData StructuresAlgorithmsXGBoostRandom ForestsTime-Series MethodsGenerative AI

Soft Skills

Client-Focused Problem SolvingCollaboration in Distributed Teams

Tools & Technologies

NumPySciPyMatplotlibScikit-LearnJupyter NotebooksBash ScriptingAWSAzureDatabricks

Industry Keywords

MLOpsData PipelinesModel Performance ManagementOpen Source ContributionsBusiness Requirements Translation

Tech Stack

Tools & technologies

AWSAzureCloudDistributed SystemsNumpyOpen SourcePythonScikit-LearnSQL

About the role

Key responsibilities & impact

Design, build, and deploy advanced machine learning and Generative AI solutions for large enterprise customers
Translate complex and ambiguous business requirements into technical specifications, model designs, and implementation plans
Build, refine, and productionize data pipelines, features, and models
Ensure robust training, evaluation, monitoring, and ongoing model performance management
Partner with data engineers, ML engineers, and cross-functional teams to implement scalable and reliable MLOps practices
Document approaches, create visualizations and presentations, and contribute to open source projects, talks, and community initiatives
Collaborate with clients, business stakeholders, data engineers, ML engineers, and distributed global teams

Requirements

What you’ll need

3–5+ years of hands-on experience building models and developing algorithms for real-world applications and data-driven optimizations
Deep knowledge of advanced mathematics, statistics, and machine learning
Expertise in deep learning, natural language processing, and computer vision
Mastery of Python and SQL
Strong computer science fundamentals in data structures, algorithms, and distributed systems
Hands-on experience with Python scripting, NumPy, SciPy, matplotlib, scikit-learn, Jupyter notebooks, and bash scripting
Practical experience with XGBoost, Random Forests, time-series methods such as Prophet, and other common modeling approaches
Familiarity with Generative AI and LLM techniques including RAG, context engineering, and agentic systems
Experience developing on AWS, Azure, or Databricks using cloud-native AI services
Technically rigorous, client-focused problem-solving approach
Ability to work in distributed, global teams and across time zones
Advanced degree or evidence of exceptional ability in engineering, computer science, mathematics, physics, chemistry, operations research, or a related field is desired, not required

Benefits

Comp & perks

Snowflake Implementation Partner of the Year recognition and AWS Premier Tier Services Partner environment
Remote-First Work Environment
401k plan with company match
Dental and Vision insurance
Home Office Equipment Stipend
Annual stipend for Learning and Development
Competitive comp
Excellent benefits
4 weeks PTO plan
10 Holidays
Other cool perks
Challenging projects, mentorship, and structured development pathways
Supportive, high-performing global team
Impactful data and AI initiatives