Data Scientist (US Value & Access Insights)

Data Scientist

Roles & Responsibilities

• Model Development & Deployment:

  Develop and deploy advanced machine learning, semantic analysis, and statistical models. You will be responsible for managing a proprietary

  AI

  engine, ensuring models are trained with the latest data and meet

  SLA

  expectations.

• Data Analysis & Modeling:

  Utilize technical skills like hypothesis testing, machine learning, and retrieval processes to identify trends and analyze relevant information. You will perform exploratory and targeted data analyses and manage the model/analytics experiment and development pipeline leveraging

  MLOps

  .

• AI & Automation:

  Collaborate with technical teams to translate business needs into technical specifications, particularly for

  AI-driven automation

  and insights. You will develop and integrate custom applications and intelligent dashboards that incorporate

  AI

  capabilities to enhance decision-making and efficiency.

• Collaboration & Expertise:

  Work with a global, cross-functional team on the

  AI

  tool's roadmap. You will act as a subject matter expert, solving development and commercial questions and staying updated with industry trends and technologies.

Qualifications

• A Master's degree with 1-3 years of experience, a Bachelor's degree with 3-5 years of experience, or a Diploma with 7-9 years of experience in computer science, statistics, or other

  STEM

  majors.
• Experience with one or more analytic tools or languages like

  R

  and

  Python

  .
• A foundational understanding of the

  US pharmaceutical ecosystem

  , patient support services, and standard datasets.
• Strong foundation in

  machine learning algorithms

  and techniques, including regression, clustering, and classification.
• Experience in

  MLOps

  practices and tools (

  e.g., MLflow, Kubeflow, Airflow

  ) and

  DevOps

  tools (

  e.g., Docker, Kubernetes, CI/CD

  ) is a plus.
• Any

  AWS Developer, Python

  , or

  ML

  certification is preferred.

Soft Skills

• Problem-Solving:

  Outstanding analytical and problem-solving skills with the initiative to explore alternate technologies and approaches.

• Communication:

  Excellent communication and interpersonal skills to collaborate with global, virtual teams and translate business needs into technical specifications.

• Initiative:

  A high degree of initiative and self-motivation with the ability to learn quickly and manage multiple priorities successfully.