Principal Data Scientist

September 15

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HP

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10,000+

💰 Post-IPO Equity on 2022-04

Description

• Are you passionate about technology and looking to work in an agile start-up environment that is built on the brand recognition, solution capabilities, and global reach of a world-class technology pioneer? • The HP Workforce Experience Platform team operates in a highly dynamic landscape that delivers a best-in-class, multi-OS Services portfolio powered by software, cloud, data analytics, and machine learning. • The AI Systems team within HP Workforce Experience Platform team is seeking a forward-thinking Data Scientist who is passionate about driving innovation at scale, solving real-world customer issues through AI/ML and delivering stellar customer experiences using one of the largest data lakes in the world. • Work closely with product management to understand product vision and user engagement strategy for the WSS Managed Insights Team. • Identify AI opportunities, prototype and iterate models, and deploy them across millions of devices. • Work with Data Scientists and Software Engineers to deliver on the Data Science Roadmap in a fast-paced environment. • Balance the business needs with technical constraints by building deep subject matter expertise for your area. • Maintain the team's focus on strategy and goal-oriented results when tackling complex problems. • Provide regular updates about program progress, issues, and risks to key stakeholders. • Act as subject matter expert through internal training and demonstration of key product functionality for support, sales, onboarding, and other cross-functional teams. • Comfortable with hands-on, day-to-day problem solving and implementing quick and effective action plans to meet short-term priorities and emerging opportunities. • Influence decision making and problem solving across teams. • Conduct A/B testing and experimentation.

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. • Passion for data science & delivering data driven outcomes. • Extensive experience using statistics, mathematics, algorithms, and programming languages. • Expert knowledge of SQL, Python and PySpark. • Strong analytical and problem-solving skills. • Fluent in structured and unstructured data, its management, and modern data transformation methodologies. • Deep understanding of current Machine Learning concepts and tools. • High EQ, ability to deal with ambiguity and work collaboratively in a high paced environment. • Create stories and visualizations to describe and communicate data insights in a clean and simple manner. • Excellent interpersonal and project management skills; ability to work across in-person and virtual team environments. • Hands-on technical skills with the inquisitiveness to learn products, work with them, and provide recommendations to drive continuous improvement. • Able to work independently yet collaborate cross-functionally in a global and multicultural environment. • Able to manage multiple work streams effectively and provide timely updates to leadership. • Comfortable and effective working in new areas that require experimentation and rapid problem solving. • Preferred: Experience in one or more machine learning frameworks, such as Tensorflow/Keras, PyTorch, Spark MLlib, or Scikit-Learn. • In-depth knowledge of one or more areas of deep learning, such as natural language generation (LLMs, Sentiment Analysis), recommendation systems, or computer vision. • Experience in Cloud computing and MLOps, especially tools such as AWS (SageMaker, EMR, Redshift), Azure, Docker, and Airflow. • Experience with Microsoft Graph API.

Benefits

• Health insurance • Dental insurance • Vision insurance • Long term/short term disability insurance • Employee assistance program • Flexible spending account • Life insurance • Generous time off policies, including; • 4-12 weeks fully paid parental leave based on tenure • 11 paid holidays • Additional flexible paid vacation and sick leave