Highlights
Innovate through AI & ML, work on cutting-edge projects, and contribute to global health initiatives.
Description
Job Summary
pJoin the Digital Product Engineering team at USP as a Data Scientist with expertise in artificial intelligence (AI), machine learning (ML), and Generative AI. Your role will focus on designing, developing, and deploying AI/ML models to solve complex business and scientific problems. You'll collaborate with data engineers to access large-scale datasets and conduct exploratory data analysis to support model development.
Responsibilities
- Design, develop, and deploy AI/ML models for business and scientific challenges
- Clean and prepare large-scale datasets for modeling and experimentation
Required Skills
- Artificial Intelligence
- Machine Learning
- Prompt Engineering
- Data Visualization
- Cloud Platforms (AWS, Azure)
Required Skills Explained
- Artificial Intelligence (AI): Understanding the principles and applications of AI to develop intelligent systems.
- Machine Learning (ML) and Deep Learning: Proficiency in developing machine learning models to solve complex business problems.
- Generative AI: Knowledge of Generative AI techniques including LLMs, RAG, prompt engineering, and vector databases like FAISS and Pinecone.
- Prompt Engineering: Ability to craft effective prompts for large language models (LLMs) and retrieval-augmented generation (RAG).
- Data Visualization Tools: Experience using tools such as Power BI, Tableau, or Plotly to present insights in a clear and actionable manner.
- Cloud Platforms: Familiarity with cloud platforms like Azure, AWS, or GCP for deploying AI/ML solutions.
- SQL and Data Manipulation: Strong skills in SQL for data extraction, transformation, and analysis.
- Programming Languages: Expertise in Python and PySpark, along with ML libraries such as scikit-learn, TensorFlow, PyTorch, and Hugging Face Transformers.
Who is this for
pThis role suits individuals with a passion for data-driven solutions and experience in AI/ML. Ideal candidates have a background in engineering, analytics, or computer science and are eager to collaborate with cross-functional teams.
Why This Job is a Good Opportunity
ulliPotential to make a significant impact on patient safety and global health through data-driven solutions.liOpportunity to work with cutting-edge technologies like Generative AI and large language models (LLMs).liCollaborative environment where you can engage with cross-functional teams across product, engineering, and business departments.liAchieve professional growth in a mission-driven organization committed to excellence and equity.liAccess to diverse data sets relevant to the life sciences and pharmaceutical industries.
Interview Preparation Tips
- Review recent advancements in AI, ML, and Generative AI technologies.
- Pretend you are explaining a complex AI model or solution to someone with no technical background.
- Create examples of how you have successfully translated business needs into data science solutions using past projects.
- Prepare stories about your collaboration skills and ability to work with diverse stakeholders.
- Discuss your experience with data visualization tools and how you effectively communicate insights.
Career Growth in This Role
pThe position offers opportunities for career growth within the field of data science, particularly in AI and ML. As a Data Scientist at USP, one can expect to deepen their expertise in Generative AI technologies such as LLMs and RAG. There are also chances to lead or mentor junior team members, contributing to the development of new products and services that impact global health.pAdditionally, roles may evolve to include more strategic responsibilities within the organization, such as overseeing data science initiatives across multiple departments or projects. The diverse and inclusive work environment at USP provides a supportive framework for continuous learning and professional advancement.
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Skills
Frequently Asked Questions
What experience is required for this role?Candidates should have 0-3 years of experience in data science, particularly with AI/ML techniques.
What kind of datasets will I work on?You will work with diverse datasets across various domains including pharmaceuticals and scientific research.
What cloud platforms are you familiar with?We use AWS, Azure, and GCP for our AI/ML workloads. Familiarity with these platforms is preferred.
