Senior Data Scientist

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Job Description:

Job Summary

This position provides leadership in the design, development and implementation of complex algorithms and advanced analytics models and solutions to yield predictive and prescriptive insights from large volume of structured and unstructured data. This position uses knowledge and expertise in analytical approaches and advanced computing methods to evaluate, estimate and run models that drive insights and empowers confidence in business decisions. This position operates and leads within a highly collaborative environment of fellow data scientists, data engineers, domain business and data leaders during every phase of the advanced analytics activities and tasks. This position guides and influences department and project teams in identifying and managing data and model management challenges and risks by facilitating collaboration with various stakeholders. This position may supervise people within the department.

Responsibilities

• Engages and collaborates with business leaders across the organization to help assess business needs and define research questions.
• Develops hypotheses, approaches (i.e., analytic plans and model development process), models, and solutions to solve problems and increase profitability.
• Builds models and tools using technical knowledge in machine learning, statistical modeling, probability and decision theory, and other quantitative techniques.
• Examines the business reality behind large sets of data and develops the appropriate method and direction to derive meaningful insights and deliver data solutions to business problems.
• Creates innovative procedures by adapting emerging tools and technologies to new modeling techniques and procedures.
• Improves upon existing methodologies by developing new data sources, testing model enhancements, and fine-tuning model parameters using Cloud-AI technologies.
• Communicates with business customers and the leadership team, who have various levels of technical knowledge, and educates them about our systems, insights, and recommendations that can inform business strategies.
• Develops strategy to monitor model and system performance/integrity and supports the analysis and integration of tools and methods to provide desired optimal results from models.
• Manages analytics projects/teams and serves as a point of contact for teams when multiple units are assigned to the same project to ensure team actions remain in synergy while communicating with stakeholders to keep the project aligned with goals.
• Acts as a project manager (as needed) of an analytics project and/or teams, responsible for the planning, procurement, quality control and execution of all components and resources needed to support the execution of data and analytics project
• Serves as a point of contact for teams when multiple units are assigned to the same project to ensure team actions remain in synergy while communicating with stakeholders to keep the project aligned with goals.

Qualifications

Requirements:

• Ability to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
• Extensive experience working with large-scale, complex datasets to create/optimize machine learning, predictive, forecasting, and/or optimization models.
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
• Strong proficiency in data management pipelines involving data extraction, analysis and transformation using either data querying languages (SQL,NoSQL, BQ), or scripting languages (e.g. Python, R) and/or statistical/mathematical software (e.g. R, Matlab, SAS).
• Hands-on experience in launching moderate to large scale advanced analytics projects in production at scale; adapts available Cloud-AI technologies and machine learning frameworks with or without the use of enterprise data science platforms.
• Direct experience in developing analytical solutions that empowers business decisions and product creation using various set of techniques (Supervised, Unsupervised, Deep Learning, NLP, Neural Networks, Graphs)
• Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams as well business audiences.
• Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.
• Proven ability to convey rigorous technical concepts and considerations to non-experts, as well as strong analytical skills, attention to detail.
• Master’s degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.

Employee Type:

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