Principal Data Scientist
Python
Ai Ml
Apache Airflow
Artificial Intelligence
Big Data
Bigdata
Cloud Data Engineering
Cloud Data Platform
Cloud Engineer
Cloud Operations
Cloud Platform
Cloud Platforms
Cloud Platforms Cloud Platforms
Data
Data Analysis
Data Analytics
Data Engineer
Data Engineering
Data Integration
Data Pipeline
Data Platform
Data Processing
Data Science
Data Warehouse
Engineering
ETL
Industrial Automation
Machine Vision
Natural Language Generation
Programming Language
Recommendation Engines
Robotics
Software Development
SQL
Job Description
Join HP and help advance AI and machine learning capabilities within the Workforce Experience Platform. In this Principal Data Scientist role on the AI Systems team, you will build and deploy models at scale across millions of devices, leveraging large data lakes and established data science practices to improve user engagement and drive better customer experiences.
What you’ll work on
- Partner with product management to understand the product vision and the user engagement strategy for the WSS Managed Insights Team.
- Spot high-impact AI opportunities, prototype and iterate models, and deploy solutions across millions of devices.
- Collaborate with Data Scientists and Software Engineers to deliver on the Data Science Roadmap in a fast-paced environment.
- Build deep subject matter expertise to balance business needs with technical constraints.
- Maintain strategy and goal-oriented execution when tackling complex, ambiguous problems.
- Run A/B testing and experimentation to validate improvements and guide decisions.
How you’ll contribute day to day
- Provide regular updates to key stakeholders on program progress, issues, and risks.
- Act as a subject matter expert by delivering internal training and demonstrating key product functionality for support, sales, onboarding, and other cross-functional teams.
- Use hands-on problem solving to implement quick, effective action plans aligned with short-term priorities and emerging opportunities.
- Influence decision making and problem solving across teams, while working independently and collaborating cross-functionally.
- Work comfortably in new areas that require experimentation and rapid iteration.
Core requirements
- Master’s degree or PhD in a highly quantitative field (Computer Science, Machine Learning, Operational Research, Statistics, Mathematics, Physics, etc.).
- 10+ years of industry experience in predictive modelling and data science roles.
- Strong passion for data science and delivering data-driven outcomes.
- Extensive experience with statistics, mathematics, algorithms, and programming languages.
- Expert knowledge of SQL, Python, and PySpark.
- Strong analytical and problem-solving skills.
- Fluency in structured and unstructured data management and modern data transformation methodologies.
- Deep understanding of current Machine Learning concepts and tools.
- High EQ, comfort with ambiguity, and collaborative work style in a high-paced environment.
- Ability to create clear stories and visualizations to communicate insights simply.
- Excellent interpersonal skills and project management experience across in-person and virtual teams.
- Hands-on technical capability and inquisitiveness to learn products, work with them, and recommend continuous improvements.
- Ability to manage multiple work streams and provide timely updates to leadership.
Tools and technologies
SQL, Python, PySpark, Tensorflow/Keras, PyTorch, Spark MLlib, Scikit-Learn, natural language generation (LLMs, Sentiment Analysis), recommendation systems, computer vision, AWS (SageMaker, EMR, Redshift), Azure, Docker, Airflow, Microsoft Graph API, and A/B testing.
Preferred experience
- Experience with one or more machine learning frameworks: Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn.
- In-depth knowledge of deep learning areas such as natural language generation (LLMs, Sentiment Analysis), recommendation systems, or computer vision.
- Cloud computing and MLOps experience, including AWS (SageMaker, EMR, Redshift), Azure, Docker, and Airflow.
- Experience with Microsoft Graph API.
Location and schedule
- Austin, TX (onsite)
- Full time
- No shift premium (United States of America)
Compensation and benefits
- Base pay range: $154,400.00 - $227,750.00 USD annually
- Additional opportunities for pay in the form of bonus and/or equity (applies to US candidates only)
- Health insurance, dental insurance, vision insurance
- Long term/short term disability insurance
- Employee assistance program
- Flexible spending account
- Life insurance
- 4-12 weeks fully paid parental leave based on tenure
- 11 paid holidays
- Additional flexible paid vacation and sick leave (US benefits overview)