Lead Data Scientist

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Job Description:

Job Summary

This position leads and advocates various data science teams on best practices around the development and implementation of advance analytic systems and predictive and prescriptive models. This position works with a team of data scientists, data analysts, data engineers, machine learning engineers, business and data domain owners, application developers, and architects in the creation and delivery of insights from large and disparate data to empower confidence in business decisions. This position leads the evaluation and adoption of emerging technologies that support the use of statistical modeling, machine learning, distributed computing, and run time performance tuning with the goal of deploying optimal processes and introducing new products and services to the market. This position supports senior leadership by planning and championing the execution of broad advanced analytics initiatives aimed at delivering value to internal and external stakeholders. This position may manage people within the department.

Responsibilities

• Leads and oversees the data analysts, data scientist team, machine learning engineers, and big data specialists in the implementation of models and systems that provide optimal results as well as scale and evolve the solutions to meet future business needs.
• Acts as subject matter expert on UPS business processes, data, and advanced analytics capabilities to scope problems, data and model requirements, and proven predictive and prescriptive techniques.
• Maintains broad understanding of implementation, integration, and inter-connectivity issues with emerging technologies to define strategies that support the creation, development and delivery of analytic solutions that meet business needs.
• Develops and prototypes algorithms to ensure analytic results satisfy problem statements and business needs.
• Interprets and analyzes large scale datasets to discover insights to support the build of analytic systems and predictive models as well as experiment with new and emerging models and techniques.
• Identifies and evaluates emerging/cutting edge open source, data science/machine learning libraries, data platforms, and vendor solutions to support the conception, planning, and prioritization of data projects across the enterprise.
• Provides thought leadership, technical guidance, and counsel for data science project teams to evaluate strategic alternatives, determine impact, recommend courses of action, and design and implement solutions.
• Champions best practices for adoption of Cloud-AI technologies, opensource software, machine learning libraries/packages, and data science platforms to derive useful information and insights that empower business decisions.
• Communicates with business customers and senior leadership team with various levels of technical knowledge, educates them about our systems, and shares insights and recommendations that can inform business strategies.
• 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.
  
  
  

Qualifications

Requirements:

• Ability to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
• Multiple years of experience working with large-scale, complex datasets to create 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
• Expertise in data management pipelines involving data extraction, analysis and transformation using either data querying languages (e.g. 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.
• Proven ability to convey rigorous technical concepts and considerations to non-experts, and strong analytical skills, attention to detail.
• Direct experience in developing analytical solutions that empowers business decisions and product creation using various set of techniques (e.g. Supervised, Unsupervised, Deep Learning, NLP)
• Excellent verbal and written communication skills with the ability to communicate data through a story framework and convey data-driven results to technical and non-technical audiences, and effectively advocate technical solutions to research scientists, engineering teams as well as business audiences.
• 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:

Permanent

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