Role: Data Scientist - Applied AI
Location: Remote
Duration: 3 Months
Overview: We are seeking an experienced Data Scientist - Applied AI to develop and operationalize machine learning and AI solutions that improve prioritization, forecasting, portfolio intelligence, operational efficiency, and decision making across the Partnering Digital Solutions ecosystem. The role will work closely with product owners, data engineers, architects, and business stakeholders to translate business challenges into scalable, production-ready AI and analytics solutions.
Key Responsibilities:
- Design, develop, validate, and deploy machine learning and applied AI solutions for business and operational use cases.
- Perform EDA, feature engineering, model selection, training, validation, and performance evaluation, optimizing models for scalability, reliability, and business impact.
- Develop predictive, classification, forecasting, recommendation, and decision-support models using structured and unstructured data.
- Translate complex business problems into analytical models, actionable insights, and intelligent workflows in partnership with product and business teams.
- Apply modern AI techniques including NLP, LLM-enabled workflows, and intelligent automation where appropriate.
- Build analytics, KPIs, dashboards, and operational intelligence capabilities that support data-driven decisions.
- Collaborate with engineering and architecture teams to deploy, monitor, and maintain ML/AI solutions in production, following enterprise AI governance and MLOps practices.
- Communicate model results and analytical insights through visualizations, presentations, and clear data storytelling for technical and non-technical stakeholders.
- Work effectively in a cross-functional Agile environment and contribute to continuous improvement of AI/ML practices and solutions.
Qualifications:
- Master's degree or PhD in Data Science, Computer Science, Statistics, Mathematics, Engineering, AI, or a related quantitative field.
- 5+ years of experience in data science, applied AI, machine learning, or advanced analytics.
- Strong hands-on experience developing, evaluating, and deploying machine learning models for business applications.
- Strong proficiency in Python, SQL, pandas, NumPy, scikit-learn, TensorFlow, and/or PyTorch.
- Experience with predictive modeling, classification, recommendation, forecasting, or decision-support solutions.
- Experience working with structured and unstructured data from multiple sources.
- Familiarity with AWS, Azure, or GCP and cloud-based AI/ML platforms.
- Strong communication and stakeholder collaboration skills.
Preferred Qualifications:
- Experience with LLMs, NLP, vector databases, RAG, agentic AI, or AI-enabled workflows.
- Experience with MLOps/LLMOps, model deployment, monitoring, observability, and lifecycle management.
- Experience with AWS SageMaker or equivalent cloud AI/ML services.
- Experience with Tableau, Power BI, or similar visualization tools.
- Experience working in product-centric Agile environments and ambiguous business settings.
- Experience in healthcare, life sciences, partnering, or business development is a plus.