We are looking for a Data Scientist to analyze large amounts of raw information to find patterns that will help improve the data to insights journey for our US Commercial Organization. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We want to see a passion for machine-learning and research. Your goal will be to help our company analyze trends to make better decisions.
What you’ll be doing:
The Manager, Data Science will be responsible for designing, executing and socializing analytical solutions to business problems across Abbvie. You will apply statistics, machine learning, and operations research techniques to enhance efforts in generating revenue, driving efficiencies, identifying cost savings, and developing products. You will work closely with IT and business stakeholders to develop analytical tools and foster the practice of data science. A candidate for this position should not only be skillful in quantitative methodologies and programming, but also have keen business acumen. The ability to work in a diverse team and the willingness to learn are key to this role.
Core Job Responsibilities:
· Develop and implement methods for extracting patterns and correlations from both internal and external data sources using machine learning toolkits
· Construct and develop predictive models that are reliable, scalable, and modular
· Maintain and optimize existing machine learning models
· Develop plan to put machine learning models into production
· Adopt new tools/techniques to increase performance, automation, and scalability
· Report, visualize and communicate results to internal stakeholders on a regular basis
· Actively participate and establish a “test and learn” team environment with a clear prioritized plan that is designed to create a bias for action (fail fast/often)
· Work with stakeholders to define business questions, requirements, timelines, objectives, and success criteria
· Examine relevant data and quickly develop an analytics plan that will answer key business questions and create value for clients
· Work with data sets of varying degrees of size and complexity, including both structured and unstructured data
· Transform data into actionable insights and recommendations. Present clear and concise results. This includes processing, cleansing, and verifying the integrity of data used for analysis
· Develop analytical solutions by using and applying appropriate methodology – including, but not limited to, regression, forecasting, clustering, decision trees, simulation, optimization, machine learning, and neural networks
· Design and define approach to scale and operationalize models for machine learning
· Masters’ degree required in quantitative fields such as Statistics, Engineering, Operations Research, Computer Science or Economics. PhD is a plus.
· 5+ years’ progressive business experiences in marketing analytics, database marketing, data engineering and predictive modeling or strong academic background.
· Ability to develop advanced machine learning models using scikit-learn, Keras, or other machine learning frameworks.
· Strong algorithmic design skills. Execute analytical experiments methodically while outputting reproducible research.
· Demonstrated proficiency in Python, R, SQL, Relational databases (Teradata, Oracle etc.), BI tools (Power BI, Qlik Sense) and IDEs like Jupyter, with experience in leveraging available packages and libraries to accelerate time to market.
· Experience with big data technologies like Hive, Impala, Hue etc.
· Experience in Pharmaceutical datasets like Patient claims and syndicated data from IQVIA (IMS) and Symphony Health Solutions a big plus.
· Strong problem solving and interpersonal skills and ability to work as part of a diverse team including IT and Line of business analytics teams.
· Bring a strong entrepreneurial spirit and ability to think dynamically.
· Strong communication skills, written and verbal.
· Project management experience; solid attention to detail and operational focus.