Data Scientist

At HPE Networking, the Digital Experience & Automation (DEA) team is reimagining how people experience support and services in a digital‑first world—setting new standards for the future of networking.We enable customers, partners, and employees through AI‑driven tools and modern platforms, transforming support into a unified, efficient, and simple experience that drives measurable value. Our mission is grounded in innovation with purpose: applying automation, AI, and data‑driven insights to simplify journeys, reduce friction, and create meaningful outcomes at every touchpoint.

What you will do:

DEA’s charter is to discover, evaluate, and scale solutions that embed intelligent technology into every interaction—delivering proactive and predictive experiences that shorten resolution times and accelerate task completion. We partner closely with technology providers, engineering, and business teams to deliver seamless omnichannel experiences and enable business transformation through data engineering, process optimization, and automation. Our work is fuelled by a passion for self‑service, intelligent automation, and building digital experiences that are intuitive, scalable, and human‑centric.

Roles and Responsibilities:
Interpret data, analyse results using statistical techniques and provideadvancedmeasurement dashboards

• Develop and implement data collection systems, data analytics and other strategies that optimize statistical efficiency and quality

• Identify, analyse, and interpret trends or patterns in complex data setsin addition to defining success metricsspanning model quality, user engagement and business outcomes.

• Work with management to prioritize business and information needs& analyse and prepare interpretations of data to use to develop conclusions

• Locate and define new process improvement opportunitiesvia creating of long-term monitoring frameworks to measure feature adoption, performance drift and business impact over time.

• Discover trends and patterns across customer journeyusing clustering, segmentation and anomaly detection and chain models of user behaviour.

• Extensive experience on machine learning and data mining algorithms like Clustering,Regression (Linear and Non-Linear), Dimensionality Reduction frameworks, Double ML, Model Calibration and fine tuning based on experiments, bias-variance trade-off in ML models,customer lifetime value modeling, survival models through hazard function optimization.

• Experience with creating and running surveys based on sampling strategies derived from power analysis,experiments based on creation of test/control groups using propensity score matching and model calibration from the results of the experiment while correcting for responder bias from the survey or experiment reach.

• Work with cross-functional teams to build data solutions that impact business decisions

• Partner with Data Engineering to design scalable data models and canonical schemassupporting analytics and AI workloads.

• DesignPower BIdashboards and advanced data visualizations to effectively communicate findings to both technical and non-technical audiences

• Conducts and facilitate (and educates and trains on) analysis, issues identification, organizational risk assessment, and decision-making processes.

• Experience working on process improvements and re-engineeringvia feedback collection through voice of customer surveys, using appropriate techniques for sample size determination and bias corrections.

• Provides consulting and analytic services to leadership.

• Providessupport, mentoringand training tojunior data scientists.
  

What you need to bring:

Required Experience/Background:

• Master’s or PhDdegree in business administration, economics, computer science, management information systems, or related field or equivalent related experience

• Overall5-7+ years of experiencein Data Science, Machine Learning or Applied Research of Measurement frameworks or systems.

• Experience with Generative AI, RAG and Multi-Turn Evaluation, Statistical modelling,DataMining,Reporting&Analyticsand Customer Journey models and frameworks.

• Strong understanding of data models, ETL pipelines,python programming,machine learning modelsfor measuring efficacy of deployed solutionsand advanced dashboarding skills for storytelling with data.

• Knowledge of statistics and experience using statistical packages for analysing datasets, includingsignificance tests, sampling strategies, power analysis, regression modelsand exploratory data analysis.

• Experience working with customer support data, conversational AI logs and omnichannel analytics, Higher Order Markov Chain models, Hazard Modelsare preferred.

• Experience onSnowflake &Databricks platform to create metrics views for business analysis,establishingconnections toPower BIandcreating business views/metrics tablesfromdeltalaketablesispreferred.

• Experience in working with Data Engineering team to define the business views needed for advanced analytics& measurement is preferred.
  

Personal Skills:

• Ability to collaborate cross-functionally in a fast-paced environment and build sound working relationships within all levels of the organization.

• Ability to handle sensitive information with keen attention to detail and accuracy. Passion for data handling ethics.

• Ability to solve complex, technical problems with creative solutions while anticipating stakeholder needs and providing assistance to meet or exceed expectations.

• Able to demonstrate perseverance and resilience to overcome obstacles when presented with a complex problem. 

• Assist in combining large data sets and data analysis to create optimization strategies.

• Comfortable with ambiguity and uncertainty of change when assessing needs for stakeholders.

• Have effective time management skills which enable you to work successfully across functions in a dynamic and solution-oriented environment while meeting deadlines

• Self-motivated and innovative; confident when working independently, but an excellent team player with a growth-oriented personality

• Will be required to routinely or customarily troubleshoot items related to applications that require independent judgement, decision-making, and unique approaches