Senior Data Science Engineer (Infrastructure & Network Analytics)

Hewlett Packard Enterprise; Bengaluru; Hybrid; INR 1,400,000 - 2,000,000; Full time

Benefits offered by this job

Comprehensive benefits suite

Personal and professional development programs

Job summary

Hewlett Packard Enterprise is seeking a highly skilled Senior Data Science Engineer to develop a Predictive Assurance platform. This role involves designing, deploying, and optimizing data pipelines and machine learning models, particularly for monitoring and analyzing enterprise-grade hardware.

The ideal candidate will have over 5 years of experience in Data Science, proficiency in Python, and familiarity with deep learning frameworks. This is a hybrid position requiring attendance at HPE offices about two days per week.

Qualifications

• 5+ years of professional experience in Data Science or Machine Learning.
• Expert-level proficiency in Python and deep learning frameworks.
• Strong background in time-series forecasting and anomaly detection.

Responsibilities

• Design and refine time-series forecasting models for optical performance.
• Develop statistical algorithms to identify degraded optics.
• Transition models from R&D to production environments ensuring scalability.

Skills

Expert-level proficiency in Python

Experience with deep learning frameworks (PyTorch, TensorFlow)

Time-series forecasting

Anomaly detection

Production-level coding experience

Familiarity with CI/CD

Proficiency in SQL

Education

PhD in Statistics, Operations Research, Computer Science or equivalent

Master’s Degree in related fields

Tools

Apache Spark

Docker

Kubernetes

Job description

Hybrid Work

This role has been designed as ‘Hybrid’ with an expectation that you will work on average 2 days per week from an HPE office.

Who We Are

Hewlett Packard Enterprise is the global edge-to-cloud company advancing the way people live and work. We help companies connect, protect, analyze, and act on their data and applications wherever they live, from edge to cloud, so they can turn insights into outcomes at the speed required to thrive in today’s complex world. Our culture thrives on finding new and better ways to accelerate what’s next. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good. If you are looking to stretch and grow your career our culture will embrace you. Open up opportunities with HPE.

Job Description

Job Family Definition

Designs, develops and applies programs, methodologies and systems based on advanced analytic models (e.g. advanced statistics, operations research, computer science, process) to transform structured and unstructured data into meaningful and actionable information insights that drive decision making.

Uses visualization techniques to translate analytic insights into understandable business stories (eg. descriptive, inferential and predictive insights).

Embeds analytics into client’s business processes and applications. Combines business acumen and scientific methods to solve business problems.

Management Level Definition

Contributions impact technical components of HPE products, solutions, or services regularly and sustainably. Applies advanced subject matter knowledge to solve complex business issues and is regarded as a subject matter expert. Provides expertise and partnership to functional and technical project teams and may participate in cross‑functional initiatives. Exercises significant independent judgment to determine best method for achieving objectives. May provide team leadership and mentoring to others.

Role Overview

We are seeking a highly skilled Senior Data Science Engineer to drive the development of our next‑generation Predictive Assurance and Real‑Time Health Analytics platform. In this role, you will design, deploy, and optimize data pipelines, statistical algorithms and machine learning models that monitor, analyze, and forecast the health of our enterprise‑grade routing fleet (including Juniper QFX Series nodes).

You will bridge the gap between heavy‑duty Data Engineering and Advanced Machine Learning, implementing stateful batch analytics engines to detect insidious regressions like memory leaks, alongside deep learning models to predict physical hardware failures in our optical layer.

What You’ll Do

• Predictive Modeling: Design and refine time‑series forecasting models (e.g., BiLSTM, Transformers, or Prophet) to predict optical performance and failure markers.
• Feature Engineering: Translate complex network telemetry (DOM metrics, FEC counters, BER, and thermal data) into actionable features for real‑time anomaly detection.
• Distributed Computing & Data Pipelines: 5+ years of production experience with Apache Spark (PySpark/Scala) utilizing advanced windowing, state manipulation, and memory‑efficient aggregations.
• Machine Learning Frameworks: Proven experience deploying LightGBM (or XGBoost) and Deep Learning frameworks (TensorFlow/Keras or PyTorch for LSTMs/BiLSTMs) into live production environments.
• Production Engineering: Lead the transition of models from R&D/Lab environments into our production Datacenter Assurance platform, ensuring scalability, low‑latency, and high availability.
• Diagnostic Analytics: Develop statistical "Health Index" algorithms to identify currently degraded optics, moving beyond simple threshold alerts to intelligent, multivariate diagnostics.
• Collaboration: Partner with network hardware engineers and software architects to understand failure signatures and integrate data‑driven insights into our monitoring workflows.

What You Need To Bring

• Experience: 5+ years of professional experience in a Data Science, Machine Learning, or AI Engineering role.
• Core Skills: Expert‑level proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
• Modeling: Strong background in time‑series forecasting, anomaly detection, and multivariate analysis.
• Engineering: Production‑level coding experience; familiarity with CI/CD, Docker, Kubernetes, and MLOps best practices.
• Data Handling: Proficiency with SQL and large‑scale data processing frameworks (e.g., Apache Spark, Kafka); bonus skills - Apache Flink, Apache Storm
• Domain Knowledge: Familiarity with network telemetry, signal processing, or hardware performance metrics is a significant plus.

Preferred Skills

• Experience with network monitoring systems or optical transceiver diagnostics.
• Expertise in statistical profiling (e.g., Z‑score, Change‑Point Detection, Dynamic Time Warping).
• Experience optimizing ML models for resource‑constrained environments or high‑throughput real‑time systems.

Domain Knowledge

• Infrastructure/Network Telemetry Domain: Experience working with time‑series metrics generated by network devices, operating systems, or cloud infrastructure (e.g., RES/RSS memory components, process‑level statistics, Junos/Linux kernel behavior).
• Optical Systems Familiarity: Basic understanding of fiber‑optic or telecom infrastructure, specifically DOM (Digital Optical Monitoring) properties.
• MLOps Mindset: Experience with containerized deployment (Docker, Kubernetes) and model lifecycle tracking tools (MLflow, Kubeflow).

Education and Experience Required

• PhD degree in Statistics, Operations Research, Computer Science or equivalent preferred and 3+ years of relevant experience. Or Master’s Degree in these areas and at least 5‑6 years of relevant experience.

Additional Skills

Accountability, Action Planning, Active Learning, Active Listening, Agile Methodology, Agile Scrum Development, Analytical Thinking, Coaching, Creativity, Critical Thinking, Cross‑Functional Teamwork, Data Analysis Management, Data Controls, Design, Design Thinking, Empathy, Follow‑Through, Group Problem Solving, Growth Mindset, Intellectual Curiosity among others.

What We Can Offer You

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

Equal Employment Opportunity

HPE is an Equal Employment Opportunity/ Veterans/Disabled/LGBT employer. We do not discriminate on the basis of race, gender, or any other protected category, and all decisions we make are made on the basis of qualifications, merit, and business need. Our goal is to be one global team that is representative of our customers, in an inclusive environment where we can continue to innovate and grow together.

Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

HPE will comply with all applicable laws related to employer use of arrest and conviction records, including laws requiring employers to consider for employment qualified applicants with criminal histories.

Recruitment Fraud Alert: We have become aware of an increase in fraudulent recruitment activities in which individuals impersonate our company or authorized recruitment agencies to offer fake employment opportunities. These scams may occur through false websites, emails, social media, or chat‑based applications and often aim to obtain personal information or money. Any reliance on fraudulent communication is at the individual’s own risk, and HPE disclaims legal liability for any resulting damages. If you suspect recruitment fraud, do not share personal information or make any payments and report the incident to your local authorities immediately.