Data Science Intern

Location: Beijing, China

Remote Type: Hybrid Work

Time Type: Part time

Job Description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

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Job Title: Data Science Intern

Location: Beijing, China
Duration: Temporary, 3–6 months | Part‑time
Reports to: Data Science Manager / Assigned Team Lead

Position summary

Participates in an internship program for a temporary duration and assists an assigned data science team. The intern contributes to team projects, receives training and mentoring, and carries out tasks under the guidance of colleagues. This role is designed to provide practical, supervised experience in data analysis and applied machine learning.

Key responsibilities

• Participate fully in the internship program for the assigned duration.

• Assist and contribute to the assigned team’s projects and deliverables.

• Work on data preparation tasks: acquisition, cleaning, transformation, and quality checks.

• Perform exploratory data analysis and produce clear visualizations and insights.

• Support development and evaluation of predictive or descriptive models (e.g., regression, classification, clustering) under supervision.

• Help document methods, code, and results in reproducible notebooks and handoffs.

• Attend team meetings, training sessions, and 1:1s with mentors; incorporate feedback.

• Follow guidance from supervisors and senior teammates when planning and executing assignments.

• Complete assigned tasks on time and flag issues or risks to the supervisor.

• Contribute to basic automation, ETL tasks, or experiment analysis as needed.

Training & mentoring

• Receive structured onboarding, training, and regular mentorship from experienced colleagues.

• Participate in knowledge‑sharing sessions, code reviews, and progress checkpoints.

• Expect progressive responsibility as skills and understanding grow during the internship.

What you’ll learn

• Practical end‑to‑end data science workflow in a team setting.

• Translating business questions into analytic plans and measurable outcomes.

• Working with real datasets, version control, and collaborative engineering handoffs.

• Communicating technical results to both technical and non‑technical stakeholders.

Required qualifications

• Currently pursuing or recently completed a degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related field.

• Basic foundation in statistics, data analysis concepts, and programming.

• Experience with Python or R and common libraries (e.g., pandas, numpy, scikit‑learn) or equivalent.

• Familiarity with SQL for data extraction.

• Strong curiosity, attention to detail, and willingness to learn.

• Good verbal and written communication skills.

Preferred qualifications

• Prior coursework or projects in machine learning, data visualization, or experimentation.

• Familiarity with Jupyter Notebooks, Git, and basic command line.

• Exposure to cloud platforms or basic data engineering concepts is a plus.

Logistics & benefits

• Temporary/paid internship.

• Mentorship and performance feedback.

• Flexible working arrangements.

• Access to learning resources and internal training.

Equal opportunity

Johnson and Johnson is an equal opportunity employer. We welcome applicants from all backgrounds and are committed to creating an inclusive environment.

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