Jobs in the United States

25+ jobs

Added just now
Software Test Automation Engineer
Booz Allen Hamilton_United States
Alexandria, VA
Added 2 mins ago
Director of Partnerships
Amperity
NY
Added 3 mins ago
Manufacturing Operations Supervisor
American Bankers Insurance Company of Florida
United States
Develop and implement process improvements, and coordinate new model introductions
Added 3 mins ago
Machine Learning Scientist, Biomolecular Structure Prediction
Profluent
Emeryville, CA
…self-directed researcher who moves quickly from hypothesis to trained model to rigorous evaluation. As an early member of the ML team, you will help shape how structure modeling fits…
Added 9 mins ago
PI
Staff Machine Learning Engineer
PayPal, Inc.
San Jose, CA
- $196,500 to $291,500 USD / year
…implementation of advanced machine learning (ML), large language model (LLM), and agentic AI systems that solve complex business and customer problems. You will translate emerging AI…
Added 10 mins ago
IC
EDA Tools Software Engineer
Intel Corporation
AZ · CA
- $128,880 to $245,160 USD / year
This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details…
Added 16 mins ago
Junior Design Verification Engineer, Amazon Leo
Amazon Kuiper Manufacturing Enterprises LLC
Austin, TX · Sunnyvale, CA
- System C, C or Matlab model : development or DV integration experience
Added 17 mins ago
S
Executive Business Center Manager
Sierra
San Francisco, CA
- $50 to $60 USD / hour
- Family: We know that balance and intensity are compatible, and we model it in our actions and processes. We are the best technology company for parents. We support and respect each other…
Added 18 mins ago
O
Principal Platform Software Engineer - JOIN OCI NASHVILLE!
Oracle
Bismarck, ND
- $104,500 to $234,600 USD / year
…AI agents, tool use, and interoperability protocols such as Model Context Protocol (MCP) and Agent-to-Agent…
Added 18 mins ago
EG
Senior Director of Finance
Eliassen Group
Bismarck, ND
- $85 to $95 USD / hour
Added 21 mins ago
Product Manager
Office Hours
Remote, United States
…sharing their knowledge through advisory work, research, and AI model…
Added 25 mins ago
Manager, Site Reliability Engineering (SRE)
Eagan, MN
Hybrid Work Model: We’ve adopted a flexible hybrid working environment for our office-based roles while delivering a seamless experience that is digitally and physically connected.
Added 30 mins ago
Account Executive
Konica Minolta Business Solutions, U.S.A., Inc.
Downers Grove, IL
Added 30 mins ago
Director, Engineering Systems Design
Invitrogen Holdings LLC
Pleasanton, CA
Strengthen model-based engineering, simulation, interface management and evidence-based decision-making.
Added 32 mins ago
AI Engineer (Active IRS MBI clearance)
Mission Bridge Partners
Remote, United States
Implement responsible AI practices, including model evaluation, guardrails, security controls, and risk mitigation.
Added 34 mins ago
SFO Office Site Security Manager
Nebius
United States
…platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML…
Added 39 mins ago
Lead Architect -GenBI Insights Platform
Travelers Indemnity Co
Hartford, CT · St. Paul, MN · Hunt Valley, MD
Extensive experience working in an agile operational model.
Added 41 mins ago
Principal Product Manager
Hewlett Packard Enterprise
Spring, TX · Ft. Collins, CO · Andover, MA
Lead the agentic AI roadmap: bring secure agent runtimes, model serving, and developer frameworks into the platform as supported, enterprise-ready experiences.
Added 41 mins ago
Lead Agentic AI Offensive Security Engineer
Hewlett Packard Enterprise
Spring, TX · San Jose, CA · Durham, NC · Andover, MA · Fort Collins, CO · Frisco, TX
Define model-agnostic interfaces supporting commercial, cloud-hosted, and open-weight models, including routing, fallback, and workload-based selection.
Added 41 mins ago
Principal Agentic AI Security Engineer
Hewlett Packard Enterprise
Spring, TX · San Jose, CA · Frisco, TX · Ft. Collins, CO · Alpharetta, GA · Durham, NC
The role focuses on system architecture, agent orchestration, model-agnostic AI integration, deterministic execution, and the engineering of secure and reliable platforms for complex…
Added 46 mins ago
Full-Stack Developer Lead
Companies, Inc.
Dallas, TX · Atlanta, GA
2020 Companies is looking for a Full-Stack Developer Lead: a builder who can also lead. You will design and ship the applications our field teams, clients, and internal teams use, from the…
Added 1 hour ago
Senior Product Manager, Health and Telemetry
Ford
Dearborn, MI · Dearborn
…integrating hardware, software and services across Ford Blue, Model e and Ford Pro. These products and services allow Ford's retail and commercial customers to customize their vehicles like…
Added 1 hour ago
Strategic Business Development Representative
Algolia
NY
Algolia’s flexible workplace model is designed to empower all Algolians to fulfill our mission to power search and discovery with ease. We place an emphasis on an individual’s impact,…
Added 1 hour ago
Software Engineer III (Agentic AI)
UKG
Seattle
…integrate with enterprise systems through tools, APIs, and Model Context Protocol (MCP) servers. Implement custom tools, skills, and plugins that extend agent capabilities across UKG's HCM…
Added 1 hour ago
Senior Customer Success Analyst
Centric Software, Inc.
Remote, United States
Analyze drivers of client churn and develop a client health score model to improve forecasting and proactive engagement strategies.

Senior Data Scientist

United States

Compensation for this role is based upon experience, qualifications, location, and education and typically ranges from $140,000 to $160,000.

Apply About employer

Applications open in a new tab.

Job details

Pay: Compensation for this role is based upon experience, qualifications, location, and education and typically ranges from $140,000 to $160,000.
Apply by: Dec 3, 2026
Experience: Experience: 4+ years of professional experience in Data Science, Machine Learning, Applied Statistics, Advanced Analytics, or a closely related field.
Posting language: English
Posted: Nov 4, 2026

Original job description

At SOM, we are a collective committed to shaping a better future for our clients, communities and planet. We aspire to create the most sustainable, impactful work through creative, interdisciplinary teams with all the resources and diversity of a global firm. We value those who are passionate about excellence, innovation, integrity, inclusivity, and collaboration. Together we can achieve great things.

Success at SOM Means

Ideas: We believe in a meritocracy of ideas. We look to everyone to actively contribute to the discourse in the firm.
Knowledge: We believe that expertise is the result of lifelong learning. We are not expected to know everything, but rather to passionately pursue answers, develop new skills and deepen our knowledge.
Product: We strive for excellence in the concept, quality, and delivery of our work.
Individual: We value individuals who bring the highest standards of professionalism and personal integrity in the way they work. Each person can develop and contribute their wealth of attributes, skills and knowledge to support the overall health of the firm.
Team: We value the power of interdisciplinary integration. A positive team culture in which everyone collaborates openly towards common goals is essential.
Firm: We have a history of making transformative contributions to the profession and our communities. We are constantly innovating and attempting to bring new approaches, solutions and processes to our work.

Position Responsibilities

Advanced Analytics & Machine Learning: Develop and implement statistical, predictive, optimization, machine learning, and AI solutions that address meaningful business and design challenges. Select methods based on the problem and available data rather than applying technology for its own sake.
End-to-End Project Ownership: Independently drive data science projects from problem discovery and data exploration through modeling, validation, deployment, and adoption. Work effectively through ambiguity, identify missing information, and determine practical next steps with limited day-to-day direction.
Project Management & Problem Solving: Define scope, identify risks and dependencies, break ambiguous problems into concrete deliverables, and communicate progress and blockers clearly. Use documentation, experimentation, available tools, and targeted collaboration to independently investigate unfamiliar problems.
Predictive Modeling & Experimentation: Build, validate, and evaluate predictive and statistical models using rigorous analytical methods. Establish appropriate baselines, design experiments, select meaningful evaluation metrics, and communicate assumptions, limitations, and uncertainty.
Production Machine Learning: Develop analytical and machine learning solutions with production use in mind, including reproducibility, testing, versioning, deployment, monitoring, and maintainability. Work within shared engineering standards and contribute to improving those standards over time.
Data Analysis & Quality: Mine, interrogate, and combine data from multiple systems. Perform exploratory analysis, feature engineering, QA/QC, and validation to determine whether available data is reliable and appropriate for analytical use.
Data Products & Visualization: Translate analytical work into usable applications, APIs, datasets, reports, dashboards, or other decision-support tools. Communicate findings clearly to both technical and non-technical audiences.
Cross-Functional Collaboration: Work closely with Data Engineering, DevOps, technology teams, and business stakeholders to support secure, sustainable deployment and integration of data science solutions.
Business & Industry Understanding: Develop expertise in SOM’s business, architecture and design practices, project delivery, and operational processes in order to identify increasingly valuable applications of data science.
Data Governance & Documentation: Follow established security, governance, privacy, and documentation standards. Maintain clear documentation for models, analytical workflows, assumptions, dependencies, and production processes.
Ownership: Take responsibility for outcomes, not just assigned tasks. Proactively identify problems, recommend solutions, and follow work through implementation and adoption.
Technical Judgment: Develop and communicate informed technical opinions while remaining open to feedback, alternative approaches, and new evidence.
Mentorship & Knowledge Sharing: Share analytical techniques and best practices with colleagues and contribute to increasing data and AI literacy across the firm.
Continuous Improvement: Stay current with developments in data science, machine learning, AI, and analytical engineering, and help improve SOM’s tools, practices, and development standards over time.

Leadership

Inspires and leads others by example, participates in staff mentoring and training, clearly defines team member expectations and responsibilities, empowers others, and delegates where appropriate based on team members’ recognized abilities and potential.
Develops and/or manages, in collaboration with team members, a clear and consistent work plan to achieve the project budget, deliverables, and schedule.
Actively engages in internal and external professional development opportunities.
Contributes to the implementation of sustainable strategies in all project assignments and the associated development of staff knowledge.
Contributes to the development of standards, policies, and procedures.

Minimum Qualifications

Experience: 4+ years of professional experience in Data Science, Machine Learning, Applied Statistics, Advanced Analytics, or a closely related field. Demonstrated ownership and complexity of work are more important than years of experience alone.
Applied Modeling: Experience developing and evaluating statistical or machine learning models that solve real-world problems and support measurable business or operational outcomes.
Production Experience: Experience moving analytical or machine learning work beyond experimentation into production or regular business use. Familiarity with testing, reproducibility, deployment, monitoring, or related ML engineering practices.
Programming: Strong proficiency in Python and SQL, with experience working with common data science and machine learning libraries and large datasets.
Data Platforms: Experience working with modern cloud data platforms or analytical environments such as Databricks, Snowflake, AWS, Azure, or comparable technologies.
Statistics & Machine Learning: Strong grounding in statistical reasoning, model evaluation, feature engineering, experimentation, predictive modeling, and appropriate machine learning techniques.
Initiative & Resourcefulness: Demonstrated ability to work independently, investigate unfamiliar problems, learn new tools and techniques, and make progress without requiring detailed step-by-step direction.
Judgment: Ability to evaluate multiple technical approaches and recognize when a simpler analytical or rules-based solution is more appropriate than machine learning.
Communication: Clear and direct communicator who can collaborate effectively across technical teams and non-technical leadership.
Collaboration & Growth: Comfortable working in a collaborative environment, receiving feedback, working within shared engineering standards, and progressively taking greater ownership as the team’s data science capability matures.
Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering or a related quantitative field, or equivalent professional experience.

Other Preferred Qualifications

Experience with Databricks, Spark/PySpark, MLflow, or similar machine learning and distributed data platforms.
Familiarity with modern analytics engineering and development practices, including dbt, Git, automated testing, and CI/CD.
Experience building analytical applications or internal data products using tools such as Streamlit or similar frameworks.
Experience with optimization, forecasting, experimentation, causal inference, NLP, or generative AI.
Experience working closely with Data Engineering or ML Engineering teams to productionize models.
Experience with cloud platforms such as AWS or Azure.
Interest in architecture, engineering, design, sustainability, or the built environment.

Compensation for this role is based upon experience, qualifications, location, and education and typically ranges from $140,000 to $160,000.

For more about SOM: www.som.com

Apply About employer

More about this job

Skills

Project management
Problem solving
Documentation
Data analysis
Work analytically
Data engineering
Production processes
Process improvement
Coaching
Machine learning
Statistics
ML
Python
SQL
Databricks
Snowflake
AWS
Microsoft Azure
Work independently
Communication skills
Leadership
Collaboration
Computer science
Apache Spark
PySpark
Mlflow
dbt
Git
Test automation
CI/CD
Forecasting
Natural language processing

Report this job