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IQVIA

Data Science Engineer (Hybrid/Remote)

Posted 10 Days Ago
Be an Early Applicant
Remote
2 Locations
Mid level
Remote
2 Locations
Mid level
The Data Science Engineer will lead client projects focused on data privacy and provide data science support for scalable architectures and workflows. Responsibilities include analyzing data re-identification risks, developing data processing solutions, and ensuring compliance with privacy regulations. The role involves collaboration and documentation of processes and methodologies.
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Role summary

The key functions of this role are two-fold: 

Client project delivery: Leading and facilitating deliveries of privacy-focused client projects, including data privacy analysis, data de-identification/anonymization, and privacy engineering and advisory work. This role may involve leading projects, as well as providing technical and methodology support to project leads, and with time, reviewing and providing oversight for other’ client work.

Data science support and DataOps: Supporting efforts towards designing and implementing scalable data architectures, data processing workflows, and data pipelines which align with best practices in data security, privacy, and compliance. These efforts may be internal to PAI or be in support of client project delivery. This role may also require aspects of DevOps, including monitoring data pipeline or application performance and identifying and resolving issues as they arise. This role may also involve developing and maintaining data-driven applications and APIs.

Must-have skills

Education
Bachelor's or Master's degree in Computer Science, Software Engineering, Mathematics, Statistics, Physics, or a related field

Client project delivery
- Ability to formulate and execute project plans independently or with moderate oversight
- Ability to document findings clearly and concisely
- Strong written and verbal communication, presentation skills
- Ability to effectively communicate findings to stakeholders with different levels of technical knowledge and understanding

Data science support and DataOps
- Proficiency in programming languages such as Python, Java, and SQL
- Knowledge of cloud computing platforms such as AWS, GCP, or Azure
- Knowledge of data warehousing and data modeling techniques
- Knowledge of software development best practices
- Ability to tailor insights and communications to multiple audiences, e.g., delivery leads, methodology leads, management.

 Job responsibilities

Client project delivery (~50% of time)
- Lead client-facing interactions to understand clients’ needs
- Analyze the re-identification risk of clients’ data sets using proprietary PAI methodology
- Present data de-identification solutions to clients
- Document re-identification risk analysis results in client-facing reports
- Transform data in alignment with established de-identification strategies
- Review and provide feedback on deliverables of other project leads
- Support delivery leads through application of PAI technology and methodology, and subject matter expertise in privacy field
- Facilitate privacy engineering and serve as a trusted advisor on data privacy for clients

Data science support and DataOps (35-40% of time)
- Assist in design and maintenance of scalable data architectures that support efficient data processing and analysis
- Develop and implement automated data processing workflows with a focus on privacy-by-design
- Collaborate with data scientists and other stakeholders to ensure that data is properly collected, processed, and stored
- Where appropriate, translate specifications into technical requirements that support development of software-driven proof-of-concept (POC) solutions
- Work with project leads and stakeholders to ensure data security and compliance with regulations such as GDPR and HIPAA
- Developing and maintaining documentation for all processes and procedures

 Nice-to-have skills

Data science support and DataOps
- Awareness of state-of-the-art in privacy-enhancing technologies
- Experience with Atlassian suite (Jira, Confluence) and Agile development practices
- Experience with software version control / build / deployment principles and tooling, e.g., Git, Jenkins, Docker
- Experience with commonly used packages in data science, e.g., NumPy, Pandas, Jupyter Notebook, Matplotlib, scikit-learn
- Experience with commonly used packages in AI/ML model training and evaluation, e.g., PyTorch
- Experience with unit, regression testing in software, e.g., unittest, pytest

IQVIA is a leading global provider of clinical research services, commercial insights and healthcare intelligence to the life sciences and healthcare industries. We create intelligent connections to accelerate the development and commercialization of innovative medical treatments to help improve patient outcomes and population health worldwide. Learn more at https://jobs.iqvia.com

Top Skills

AWS
Azure
Confluence
Docker
GCP
Git
Java
Jenkins
JIRA
Jupyter Notebook
Matplotlib
Numpy
Pandas
Pytest
Python
PyTorch
Scikit-Learn
SQL
Unittest

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