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Data Analyst – AI & Data Science (Senior / Staff Level)

Qualcomm

Data Analyst – AI & Data Science (Senior / Staff Level)

Qualcomm

Taipei, Taipei City, Taiwan

·

On-site

·

Full-time

·

2mo ago

Company:

Qualcomm Semiconductor Limited:

Job Area:

Information Technology Group, Information Technology Group > IT Engineering

General Summary:

We are seeking a highly skilled Senior / Staff Data Analyst with expertise in AI and Data Science to design, implement, and optimize advanced analytics and machine learning solutions. This role requires strong technical proficiency, business acumen, and innovative thinking to deliver actionable insights and drive data-driven decision-making. The position involves understanding business requirements, translating them into data-driven strategies, and developing solutions that improve operational efficiency and overall business performance.

Responsibilities:

  • Build and deploy AI/ML workflows, leveraging Large Language Models (LLMs) and AI agents for automation.
  • Develop and maintain scalable, reliable data pipelines using tools such as Python, Spark, and Kafka to ensure data accessibility and performance for machine learning applications.
  • Gather and interpret business requirements to design data-driven solutions that address key challenges and improve efficiency.
  • Collect, clean, and analyze large datasets (structured and unstructured) to identify trends, patterns, and actionable insights.
  • Develop predictive and prescriptive models to support decision-making and optimize business processes.
  • Create dashboards, reports, and visualizations using tools like Tableau or Power BI to communicate insights effectively to stakeholders.
  • Collaborate with cross-functional teams—including business units, data engineers, and software developers—to ensure alignment between analytics solutions and organizational goals.
  • Partner with cross-functional teams—including data engineers, software developers, and business stakeholders—to define requirements, integrate systems, and present findings in clear, actionable formats.

Qualifications:

  • Expertise in Python and the data/ai ecosystem libraries and frameworks.
  • Solid foundation in data architecture, statistics, machine learning, deep learning, and data science techniques.
  • Experience handling large scale data distributed data for deep analysis.
  • Working knowledge of LLMs, Agents and Agentic workflows.
  • Demonstrated capability to develop scalable data integrations following best practices for data quality, security, and governance in enterprise environments.
  • Hands-on experience with tools and platforms such as:Big Data Technologies: Apache Spark, Hive, Presto
  • Cloud Platforms: AWS, Azure, GCP
  • Databases: SQL, NoSQL, vector databases
  • Visualization Tools: Tableau, Power BI
  • Exceptional analytical and problem-solving skills with a focus on delivering production-grade solutions that drive measurable business impact.
  • Minimum 3+ years of hands-on experience in data science, machine learning, or advanced analytics, preferably in enterprise-scale environments.

Education:

  • Bachelor’s degree in Computer Science, Engineering, Statistics, Applied Mathematics, or a related quantitative field.

Minimum Qualifications:

  • 4+ years of IT-related work experience with a Bachelor's degree. OR
    7+ years of IT-related work experience without a Bachelor’s degree.

Physical Requirements:

  • Frequently transports and installs equipment up to 20 lbs.

Applicants: Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries).

Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law.

To all Staffing and Recruiting Agencies: Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications.

If you would like more information about this role, please contact Qualcomm Careers.

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About Qualcomm

Qualcomm

Qualcomm

Public

Inventing the technologies the world loves.

10,001+

Employees

San Diego

Headquarters

Reviews

3.6

5 reviews

Work Life Balance

4.0

Compensation

4.0

Culture

2.5

Career

3.0

Management

2.5

Pros

Good work-life balance

Real engineering work with technical challenges

Good compensation

Cons

Slow processes and bureaucracy

Poor management and planning

Cross-team dependencies and alignment issues

Salary Ranges

1 data points

Junior/L3

Junior/L3 · Data Scientist

0 reports

$215,000

total / year

Base

$170,000

Stock

$30,000

Bonus

$15,000

$182,750

$247,250

Interview Experience

8 interviews

Difficulty

3.4

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 50%

Negative 50%

Interview Process

1

Application Review

2

Recruiter Screen

3

Technical Phone Screen

4

Technical Interview/Onsite

5

Team Matching

6

Offer

Common Questions

Coding/Algorithm

Technical Knowledge

System Design

Behavioral/STAR

Past Experience