About the role

AI summarised

This role is for a Customer Success & Insights Engineer at HP, focusing on developing AI-driven solutions to enhance customer intelligence and generate predictive insights. The engineer will analyze complex data sets, build machine learning models, and create visualizations to drive business decisions, working with large language models and agentic AI capabilities.

ElectronicsFull-timeData & Information Technology

Key Responsibilities

Collaborates with stakeholders to understand business requirements and develop AI-driven solutions to surface insights; drives action, defines success measures and tracks effectiveness of solution
Develops monitoring metrics to reflect real-world model performance and makes recommendations to shape the future direction of models and digital solutions.
Delivers predictive and prescriptive models of high complexity to surface insights; drives action, defines success measures and tracks performance of models.
Data mine and analyze monthly calls, returns, telemetry and sentiments (nps, web reviews) data to provide holistic and detailed analysis of product quality to generate impactful and actionable insights
Enable predictive data analytic capabilities using printer telemetry data.
Ties insights into effective visualizations communicating business value and innovation potential.
Solves difficult and complex problems with a fresh perspective, demonstrating good judgment in selecting creative solutions and managing projects independently.
Provides guidance, training and mentoring to less experienced staff members.

Requirements

Four-year or Graduate Degree in Mathematics, Statistics, Computer Science, Information Technology, Software Engineering, or any other related discipline or commensurate work experience or demonstrated competence.
Typically has 5-7 years of work experience, preferably in data analytics, statistical modeling, machine learning, or a related field.
Strong foundation in data science and core machine learning concepts.
Experience with large language models, multi-modal modals, prompt engineering, vector databases, data analysis / visualization tools and software like Power BI, Looker, Databricks etc
Proficiency in SQL for data extraction and manipulation, computer programming languages such as Python, R
Attention to detail and a commitment to data accuracy.
Proficient in PowerPoint, Excel and related IT tools for data mining & analysis.
Ability to effectively communicate, drive discussions & provide options at management levels