Senior Data Scientist Full-time NEW

Senior Data Scientist

Come to work each day with an inclusive and collaborative business technology team. As a Senior Data Scientist in AbbVie Business Technology Solutions (BTS), you will have opportunities to contribute to the digital transformation of a leading biopharma company, helping to create solutions that impact patients and their communities for the better.

A successful candidate will bring advanced analytics knowledge of best-in-class data science methodologies, deep understanding of AI/ML space, proven history of solving business problems using data science and ability to work with cross-functional teams to deliver and execute complex analytics problems.

Responsibilities:

• Discern whether a business problem needs a classical Machine Learning approach, a Generative AI, or Agentic solutions.
• Apply structured frameworks like CRISP-DM or other approach to deliver value in a consistent, process driven way.
• Develop processes and tools to monitor and analyze model performance and data accuracy and lead the advanced analytics framework through AI/ML.
• Work with complex data sets (unstructured and structured data) to solve business use cases by establishing robust measurement frameworks and deliver business value with data-driven insights to senior leaders.
• Perform data discovery and analysis to discover trends and patterns, meaningful insights and apply strong knowledge of data science for making informed decisions.
• Design and develop data visualizations to effectively communicate insights to both technical and non-technical audiences.
• Establish and follow data science's best practices including peer review, code review, documentation, coding standards, data quality and ensure reproducibility and compliance.
• Serve as internal Data Science SME and on advanced analytics platform like Dataiku and drive the self-service citizen data science COE with office hours training and establish data governance around the curated datasets and metrics, and best practices on taxonomy.
• Initiate and drive projects with minimal oversight and guidance.
• Tools and skills you will use in this role:
• Data Prep and Data science platforms like Databricks or SageMaker
• Data Visualization Tools like Power BI, Tableau, and ThoughtSpot
• Advanced SQL, Python, Spark, and a broad array of ML frameworks
• Lakehouse data storage patterns like Iceberg and Delta
• JIRA, CI/CD and Agile project methodology
• Predictive and prescriptive models, other statistical models, and knowledge in data science in general
• Cloud environment (AWS) with large datasets and with streaming data architectures.
• Large Language Models and Generative AI
• ML frameworks (Scikit-Learn, NumPy, SciPy, Pandas, XGBoost, TensorFlow, PyTorch, MXNet, LLM)
• Classical ML validation as well as Agentic and Generative AI evaluation techniques.
• ML Registries like MLFlow

Qualifications

Required:

• Bachelor's Degree with 7 years of experience; Master's Degree with 6 years of experience; PhD with 2 years of experience.
• Respective years of working experience in data science framework and knowledge of using all the statistical or AI/ML learning models to address business use cases with extensive experience with statistical/analytical methodologies and machine learning algorithms (e.g. classification, regression, clustering, forecasting, feature selection/engineering, deep learning, time-series analysis, hypothesis testing, anomaly detection).
• Respective years of experience in advanced SQL, Python, Spark, and a broad array of ML frameworks.
• Respective years of experience with advanced analytics and data science platforms like SageMaker.
• Respective years of experience with data lakes like Iceberg or Delta.
• Respective years of experience in developing and deploying solutions in a Cloud environment (AWS, Azure) with large datasets and with streaming data architectures.
• Respective years of experience in using MLflow for model registry, experiment tracking, and model validation.
• Minimum 2 years of experience with GenAI application development, LLM prompt engineering, LLM-based solution architecture like RAG, developing Chatbots and AI agents using both unstructured and structured data.
• Experience in data mining, data discovery, building curated data sets, insight generation, advanced analytics, and data science.
• Self-starter, comfortable with ambiguity, experience initiating and driving projects with minimal oversight and guidance.

Preferred:

• Experience with Pharma data, including insights into commercial sales and field operations is a plus.
• Respective years of experience with Data Visualization tools like Power BI and Tableau or ThoughtSpot.
• Consulting experience in Data science and Advanced Analytics domain.
• 5+ years of working experience in data science framework and knowledge of using all the statistical or AI/ML learning models to address business use cases with extensive experience with statistical/analytical methodologies and machine learning algorithms (e.g. classification, regression, clustering, forecasting, feature selection/engineering, deep learning, time-series analysis, hypothesis testing, anomaly detection).
• 5+ years of experience in advanced SQL, Python, Spark, and a broad array of ML frameworks.
• 3+ years of experience with advanced analytics and data science platforms like Dataiku.
• 3+ years of experience with Data Visualization tools like Power BI and Tableau or ThoughtSpot.
• 3+ years of experience with data lakes like Iceberg or Delta.
• 3+ years of experience in developing and deploying solutions in a Cloud environment (AWS, Azure) with large datasets and with streaming data architectures.
• 3+ years of experience in using MLflow for model registry, experiment tracking, and model validation.

Pay Range: $109500 – 208500 USD