Senior AI Data Scientist

Powerhouse Institute Inc.; Washington (District of Columbia); Hybrid; USD 145,000 - 175,000; Full time

Job summary

Powerhouse Institute Inc. is seeking a senior data science leader to drive enterprise AI strategy and deliver production ML solutions in a fully remote role based in the U.S.

You will guide ML model development, governance, and analytics storytelling for executive stakeholders. The ideal candidate has 10+ years in data science/AI, strong Python and MLOps experience, and a track record of deploying scalable AI systems across cloud platforms.

Qualifications

• Must be a U.S. Citizen or Permanent Resident (Green Card holder).
• Must be able to obtain/hold Public Trust or higher clearance.
• Based in the U.S. for the last 3 of the past 5 years.
• 10+ years of experience in data science, ML, or applied AI with deep ML/DL/LLM expertise.
• 6+ years leading enterprise-scale data science initiatives.
• Expert-level Python proficiency with production-grade solutions.
• Proven experience deploying ML models in production.
• Strong MLOps experience and lifecycle management.
• Experience with LLMs, NLP, or generative AI.
• Experience with AI governance, model risk, and ethical AI.
• Experience with MLOps frameworks (MLflow, Kubeflow, Azure ML, SageMaker).
• Experience with big data tools (Spark) and clouds (AWS, Azure, GCP).
• Strong SQL skills for data extraction and analysis.
• Proficiency with Power BI or Tableau for visualization.
• Familiarity with federal AI governance frameworks (NIST AI RMF, OMB guidance).
• Experience handling sensitive data (PII protection).
• Experience with generative AI tooling, RAG frameworks, embeddings, vector databases.
• Strong statistics, experimentation design, and model evaluation skills.
• Ability to process high-volume data and derive insights.

Responsibilities

• Analyze unstructured and semi-structured data using advanced algorithms in distributed and cloud environments.
• Lead enterprise data science and AI strategy; advise on analytics adoption.
• Drive AI/ML initiatives from concept to MVPs and production-ready solutions.
• Translate business problems into analytical frameworks and scalable AI solutions.
• Design, build, and deploy ML solutions (predictive modeling, NLP, LLMs, recommender systems).
• Apply advanced data science methods (deep learning, time series, A/B testing, experimentation).
• Lead hands-on model development in Python with reusable, tested code and feature engineering.
• Collaborate with AI/engineering teams on end-to-end MLOps: versioning, training pipelines, monitoring, drift detection.
• Work with data engineers to build scalable data platforms and cloud-based pipelines.
• Establish model governance, explainability, data quality, and auditability standards.
• Communicate insights to executives with data storytelling and visuals.
• Mentor data science talent and lead cross-functional teams on high-impact AI projects.

Skills

Python

MLOps

SQL

Data Visualization

Cloud Platforms

NLP

LLMs

RAG

Vector Databases

Statistics

Education

BS or MS in data science / CS / statistics

Tools

MLflow

Kubeflow

Azure ML

SageMaker

Spark

Job description

Fully Remote Remote - Washington DC Metro Area (DMV), DC

Job Type

Full-time

Description

NOTE: This opportunity is full-time employment position only (no 1099 or C2C engagements, or third parties or staffing agencies, please). The candidate MUST be a U.S. Citizen or Permanent Resident (Green Card holder). This is a remote opportunity; candidate must be based in the U.S.; have resided in the U.S. for at least 3 years in the past 5 years; ET time zone work schedule.

Daily Responsibilities

• Analyzes unstructured and semi-structured data, applying creativity to large-scale analysis for high-value use cases using advanced algorithms in distributed and cloud-based infrastructures. s. Utilizes advanced tools for interpreting complex data, delivering recommendations for business decisions. Experience in software development, data transport APIs, Cloud-based tools, and visual analytics, with expertise in open-source stacks, Windows development, and various data analysis technologies.
• Execute and advance the enterprise data science and AI strategy aligned to organizational goals, serving as a trusted advisor on advanced analytics, machine learning, and AI adoption.
• Lead high-impact AI/ML initiatives across business and technology teams, delivering proofs of concept and MVPs that mature into scalable production solutions.
• Translate complex business challenges into analytical frameworks and scalable AI-driven solutions that support strategic decision-making.
• Design, develop, and deploy advanced machine learning solutions, including predictive modeling, forecasting, NLP, large language models (LLMs), recommendation systems, optimization models, RAG, and other AI-powered applications.
• Apply advanced data science techniques including deep learning, ensemble methods, time series analysis, experimentation, A/B testing, and statistical modeling.
• Lead hands-on model development in Python, establishing best practices for reusable code, testing, reproducibility, feature engineering, and utilization of modern data science frameworks and libraries.
• Partner with AI and engineering teams to implement end-to-end MLOps practices, including model versioning, automated training and deployment pipelines, monitoring, drift detection, and continuous model improvement.
• Collaborate with data engineers and architects to build scalable data platforms, pipelines, and cloud-based solutions that support large-scale structured and unstructured data.
• Establish and enforce standards for model validation, explainability, interpretability, data quality, governance, responsible AI, bias mitigation, transparency, and auditability.
• Communicate complex analytical insights to executive and non-technical stakeholders through effective data storytelling, visualization, and strategic recommendations.
• Mentor and develop data science talent while leading ross-functional teams to deliver high-impact data science and AI solutions.

Requirements

• Must of a U.S. Citizen or Permanent Resident (Green Card holder), as mandated by our government client.
• Must be able to complete/pass/hold at a minimum a Public Trust Investigation / background check. An active Public Trust or higher is preferred.
• Must be based / reside in the U.S.
• 10+ years of experience in data science, machine learning, or applied AI with deep expertise in machine learning, deep learning, and LLM-based approaches.
• 6+ years of demonstrated experience leading enterprise-scale data science initiatives.
• Expert-level proficiency in Python for data science and machine learning, including hands-on Python experience delivering production-grade data science solutions.
• Proven experience building and deploying ML models in production environments.
• Strong experience with MLOps tools, pipelines, and lifecycle management.
• Experience with LLMs, NLP, or generative AI applications.
• Experience in AI governance, model risk management, or ethical AI.
• Proven experience implementing MLOps frameworks and production ML systems (e.g., MLflow, Kubeflow, Azure ML, or SageMaker).
• Experience with big data tools (e.g., Spark) and cloud platforms (AWS, Azure, GCP).
• Strong SQL skills for data extraction, transformation, and analysis.
• Proficiency with data visualization and BI tools (e.g., Power BI, Tableau).
• Familiarity with federal AI governance frameworks, including the NIST AI Risk Management Framework and OMB AI guidance.
• Experience working with sensitive data, including PII safeguards such as anonymization, masking, and data loss prevention.
• Experience with generative AI tooling, including RAG frameworks, embedding models, and vector databases.
• Strong foundation in statistics, experimentation design, and model evaluation (including precision, recall, F1 score, and related performance metrics.
• Ability to process high-volume data collections and streams, making discoveries in the realm of big data.
• Requires strong technical and computational skills for coding, designing, and deploying sophisticated applications in unstructured data analysis.
• Excellent analytical skills, attention to detail, and strong problem-solving abilities.
• Excellent communication and collaboration skills to communicate complex analytical insights to executive and non-technical stakeholders. Ability to translate ambiguous business questions into analytical solutions.
• BS or MS degree (preferred) in data science, computer science, statistics or related field.

Compensation decisions depend on a wide range of factors, including but not limited to skill sets, experience and training, security clearances, licensure and certifications, and other business and organizational needs. $145k -$175k.