Data Scientist VI

Job Summary

This senior individual contributor is primarily responsible for overseeing the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats. This role is also responsible for leading and overseeing the development of detailed problem statements outlining hypotheses and their effect on target clients / customers, serving as a lead expert in the analysis and investigation of complex data sets, overseeing the selection, manipulation and transformation of data into features used in machine learning algorithms, training statistical models, directing the deployment and maintenance of reliable and efficient models through production, ensuring and leading the verification of model performance, and building and maintaining partnerships with internal and external stakeholders across domains to develop and deliver statistical driven outcomes.

Essential Responsibilities

• Promotes learning in others by communicating information and providing advice to drive projects forward; builds collaborative, cross-functional relationships. Solicits and acts on performance feedback; provides actionable feedback to others, including upward feedback to leadership; influences, mentors, and coaches team members. Practices self-leadership; creates, evaluates, and responds to the strengths and weaknesses of self and unit or team members. Leads the adaptation to competing demands and new responsibilities; adapts to and learns from change, challenges, and feedback. Fosters open dialogue amongst team members.
• Drives the execution of multiple work streams by identifying member and operational needs; translates business strategy into actionable business requirements; develops and updates new procedures and policies. Gains cross-functional support for objectives and priorities; determines and carries out processes and methodologies; solves highly complex issues; escalates and resolves issues as appropriate; sets standards and measures progress. Develops work plans to meet business priorities and deadlines; coordinates, obtains and distributes resources. Removes obstacles that impact performance; guides performance and develops contingency plans accordingly; influences the completion of project tasks by others.
• Leads and oversees the development of detailed problem statements outlining hypotheses and their effect on target clients / customers by ensuring comprehensive and accurate definitions of scope, objectives, outcome statements and metrics.
• Oversees the design and development of data pipelines and automation for data acquisition and ingestion of raw data from multiple data sources and data formats by driving the transformation, cleansing, and storing of data for consumption by downstream processes; overseeing the development and optimization of diverse and complex SQL queries; and demonstrating advanced expertise of database fundamentals.
• Serves as a lead expert in the analysis and investigation of complex data sets by ensuring optimum data visualization methods are employed; determining and communicating how best to manipulate data sources to discover patterns, spot anomalies, test hypotheses, and / or check assumptions; and reviewing and verifying summaries of key dataset characteristics.
• Oversees the selection, manipulation, and transformation of data into features used in machine learning algorithms by leveraging and demonstrating advanced expertise in techniques to conduct dimensionality reduction, feature importance, and feature selection.
• Trains statistical models by selecting and leveraging algorithms and data mining techniques; overseeing model testing; ensuring the proper use of various algorithms to assess the input dataset and related features; and ensuring appropriate techniques are used to prevent overfitting such as cross-validation.
• Directs the deployment and maintenance of reliable and efficient models through production.
• Ensures and leads the verification of model performance by demonstrating advanced expertise in the practice of a variety of model validation techniques to assess and discriminate the goodness of model fit; and leveraging feedback and output to direct and strengthen model performance.
• Builds and maintains partnerships with internal and external stakeholders across domains to develop and deliver statistical driven outcomes by generating and delivering insights and values from heterogeneous data to investigate complex problems for multiple use cases; driving informed decision-making; and presenting findings to both technical and non-technical senior leadership.

Minimum Qualifications

Additional Requirements

Preferred Qualifications

#J-18808-Ljbffr