Data Scientist

Job description

Data Scientist This role has been designed as Hybrid with a requirement that you will work on average 2 days per week from an HPE office. 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, analy s e results using statistical techniques and provide advanced measurement dashboards - Develop and implement data collection systems, data analytics and other strategies that optimize statistical efficiency and quality - Identify, analy s e, and interpret trends or patterns in complex data sets in addition to defining success metrics spanning model quality, user engagement and business outcomes. - Work with management to prioritize business and information needs & a naly s e and prepare interpretations of data to use to develop conclusions - Locate and define new process improvement opportunities via creating of long-term monitoring frameworks to measure feature adoption, performance drift and business impact over time. - Discover trends and patterns across customer journey using 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 . - Exp erience 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 schemas supporting analytics and AI workloads. - Design Power BI dashboards 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-engineering via feedback collection through voice of customer surveys , using appropriate techniques for sample size determination and bias corrections. - Provides consulting and analytic services to leadership. - Provides support, mentoring and training to junior data scientists. **What you need to bring:** **Required Experience/Background:** - Master s or PhD degree in business administration, economics, computer science, management information systems, or related field or equivalent related experience - Overall 5-7 + years of experience in Data Science, Machine Learning or Applied Research of Measurement frameworks or systems. - Experience with Generative AI, RAG and Multi-Turn Evaluation , Statistical modelling, Data Mining , Reporting & Analytics and Customer Journey models and frameworks. - Strong understanding of data models, ETL pipelines, python programming, machine learning models for measuring efficacy of deployed solutions and advanced dashboarding skills for storytelling with data. - Knowledge of statistics and experience using statistical packages for analy s ing datasets, including significance tests, sampling strategies, power analysis, regression models and exploratory data analysis. - Experience working with customer support data, conversational AI logs and omnichannel analytics, Higher Order Markov Chain models , Hazard Models are preferred. - Experience on Snowflake & Databricks platform to create metrics views for business analysis , es tabli shing connect ions to P o wer B I and cre ating b usiness v iews / metri cs tables from d elta lake tables is prefe rred . - 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 wi