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Data Scientist/SR Data Scientist
3 months ago
Duties & Responsibilities
Data Science:
Executes the technical development of novel tools which incorporate models that recommend action and guide decision making.
Recommends key enablers including business process, organizational and technology.
Works with our BI analysts to apply business intelligence tools to provide dashboards to drive appropriate action and behavior, and measurement and accountability against key business initiatives.
Works together with Information Technology developers for the implementation and maintenance of back-end database and reporting/analytics environments.
Encourages and develops new ideas from the team to foster improvements through innovation.
Performs ongoing data analysis to develop a deep understanding of the impact on data with changing market and business unit dynamics.
Examines patterns in the data and coordinates with business unit to define opportunities for deep-dive analyses.
Develops and implements a process for cross-checking validity of data pulls made by other members of the Commercial Excellence Team.
Defines data requirements and appropriate modeling techniques in response to both specific, cyclic business requests and ad hoc or one-off analyses.
Develops and executes a methodology for choosing appropriate types of models based on business requests.
Designs business case-appropriate predictive models using machine learning techniques and statistical analyses.
Trains and evaluates models and deploys methods to increase accuracy where possible.
Data Stewardship:
Actively supports all aspects of the BI Data Governance Program.
Identifies causes of poor data quality management, implements solutions and communicates findings to employees, management, and stakeholders.
Ensures processes adhere to data management policy.
Collaborates with Business Process owners and Data Stewards to develop methods for synchronizing data entering company systems.
Responsible for ensuring issues and/or outages are communicated to the user community.
Participates in postmortem meetings and report out on data impacts and outages across organization in a manner which instills confidence in issue understanding, impact and next steps along with prevention/elimination recommendations.
Understands inter-relationship of systems and processes which could be corrupt data impacting events and recommend course of action.
Models the behaviors of championing data as an asset.
Regulatory:
Performs all Company business in accordance with all regulations (e.g., EEO, FDA, OSHA, PDMA, EPA, PhRMA, etc.) and Company policies and procedures.
Reports all violations immediately to management.
Documents observations and provide information to management as necessary.
Demonstrates high ethical and professional standards with all business contacts and BI employees.
Desired Skills, Experience & Abilities
Machine Learning engineering:
Experience in model tuning and optimization.
Knowledge and experience in MLOps industry best practices.
Experience with cloud-based (AWS, Azure, Google) machine learning services.
Knowledge and Experience with Databricks.
Experience in building CI/CD pipelines, especially ones utilizing machine learning components, and associated tools.
Knowledge of general application monitoring best practices and tools.
Experience with model monitoring strategies and retraining logic.
Experience in development of APIs.
Knowledge and experience in event-stream architecture and development.
Data Science:
Data mining experience using statistical software (R or Python preferred).
Strong analytical skills, to critically evaluate information gathered from multiple sources, reconcile conflicts, decompose high-level information into details, abstract up from low-level information to a more general understanding, distinguish presented user requests from the underlying true needs, and distinguish solution ideas from requirements.
Data mining technical knowledge and skills including decision trees, multivariate analysis, segmentation modeling, factor analysis, regression analysis, forecasting, and machine learning.
Intellectual curiosity and commitment to teaching data analytics concepts to others.
Communication:
Excellent interpersonal and communication skills.
Strong relationship building skills.
Strong organizational skills, detail oriented and process-driven, with an orientation toward continuous process improvement.
Exceptional problem-solving abilities and experience synthesizing disparate and sometimes potentially contradictory data and communicating this information to the business.
Data Scientist Requirements
Master's Degree in Data Science, Statistics, Computer Science or equivalent field is required, with a minimum of three (3) years of experience in related role.
In lieu of a Master's Degree, Bachelor's Degree with five (5) years work experience in data science, machine learning and MLOps Engineering.
Demonstrated experience in systems and processes, creating and executing algorithms and distilling the solutions for a business audience, process improvement, preferably within the Pharmaceutical Industry.
Demonstrated understanding and ability to apply principles, concepts, practices, and standards including knowledge and use of Animal Health or Pharma data and working knowledge of industry practices.
Demonstrated ability to communicate ideas, facts, and technical information clearly and concisely to senior management, as well as other internal customers both verbally and written.
Demonstrated excellent communication skills and ability to work with other disciplines.
Demonstrated ability to identify and analyze problems, evaluate alternatives, and implement effective solutions.
Demonstrated ability to effectively manage multiple priorities.
Ability to work independently with a high degree of accuracy and attention to detail in the fast-paced environment.
Proficiency in data mining and munging tools, especially R and Python.
Sharp analytical abilities and proven statistics skills.
Models willingness to learn and stay up to date.
Effective analytical and problem-solving skills.
History of successful performance.
Must achieve results in a highly matrixed organization.
Requires working with IT on system improvements and execution.
Ability to travel (may include overnight travel).
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