Level

HP

Applied Research - Data Scientist

AI in this role

ragai-agentsfine-tuningml-opsnlpspeech
Applied Research - Data Scientist

Description -

Job Summary
This role is responsible for conducting innovative research focused on machine learning (ML) and natural language processing (NLP), translating insights into experimentation and applying broad technical expertise to design and optimize systems. It involves developing impactful solutions with minimal oversight and contributing to the organization’s knowledge base by documenting and sharing findings.


Responsibilities
• Solve difficult and often complex problems using advanced AI technologies such as ML and NLP.
• Conduct experimental research with a broad perspective to identify innovative solutions.
• Apply wide-ranging experience to resolve complex issues creatively and effectively.
• Analyze situations or data requiring broad perspectives and innovative solutions.
• Lead large projects or processes with limited oversight from management.
• Develop and implement advanced systems for language translation, sentiment analysis, and speech recognition.
• Optimize algorithms for machine learning and predictive analytics.
• Document and share research processes and findings within the organization.
• Mentor junior researchers and provide guidance on complex projects.
• Exercise judgment in selecting methods, techniques, and evaluation criteria for obtaining results.


Education & Experience Recommended
• 10 years+ of experience
• Bachelor’s degree in engineering, computer science, information technology or a related field.

•    Advanced AI/ML: Expert in ML, Deep Learning, GenAI/LLMs, NLP, embeddings, RAG, fine-tuning, and AI agents.


Preferred Certifications
• N/A


Knowledge & Skills
• Programming Languages
• Python (Programming Language)
• Machine Learning & Deep Learning
• Natural Language Processing (NLP)
• Data Engineering
• MLOps
• Cloud Platforms
• Algorithm Design
• Generative AI & LLMs
• AI Ethics
• Product Thinking
• Collaboration & Communication
• Analytical skills
• AI agents - agentic systems
• Statistical Modeling
• Critical Thinking.


Cross-Org Skills
• Effective Communication
• Results Orientation
• Learning Agility
• Digital Fluency
• Customer Centricity

Impact & Scope

• Impacts function and leads and/or provides expertise to functional project teams and may participate in cross-functional initiatives.


Complexity
• Works on complex problems where analysis of situations or data requires an in-depth evaluation of multiple factors.


Disclaimer
• This job description describes the general nature and level of work performed in this role. It is not intended to be an exhaustive list of all duties, skills, responsibilities, knowledge, etc. These may be subject to change and additional functions may be assigned as needed by management.

#LI-POST

Job -

Software

Schedule -

Full time

Shift -

No shift premium (India)

Travel -

Relocation -

Equal Opportunity Employer (EEO) - 

HP, Inc. provides equal employment opportunity to all employees and prospective employees, without regard to race, color, religion, sex, national origin, ancestry, citizenship, sexual orientation, age, disability, or status as a protected veteran, marital status, familial status, physical or mental disability, medical condition, pregnancy, genetic predisposition or carrier status, uniformed service status, political affiliation or any other characteristic protected by applicable national, federal, state, and local law(s).

Please be assured that you will not be subject to any adverse treatment if you choose to disclose the information requested. This information is provided voluntarily. The information obtained will be kept in strict confidence.

For more information, review HP’s EEO Policy or read about your rights as an applicant under the law here: “Know Your Rights: Workplace Discrimination is Illegal"

How we rate this

Applied Research - Data Scientist at HP rates 93 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI AgentsFine TuningML OpsNLPSpeech

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. Walk me through fine-tuning a model: what data did you use, and how did you check the result?
  4. How do you monitor a model once it's live, and how do you know it needs retraining?
  5. What NLP problem have you worked on, and how did you measure whether it actually worked?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Agents, Fine Tuning, ML Ops, and NLP. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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