Lead Data Scientist

Job Description: As a leader at a Fortune Global 500 organization, you will be responsible for advocating various data science teams on best practices surrounding the development and implementation of advanced analytic systems and predictive and prescriptive models. Working closely with a team of data scientists, data analysts, data engineers, machine learning engineers, business and data domain owners, application developers, and architects, you will play a crucial role in creating and delivering insights from large and disparate data to enable confident business decisions. Your role will involve evaluating and adopting emerging technologies that support statistical modeling, machine learning, distributed computing, and run-time performance tuning to optimize processes and introduce new products and services to the market. Additionally, you will support senior leadership by planning and executing broad advanced analytics initiatives aimed at delivering value to both internal and external stakeholders. Furthermore, you may also be involved in managing people within the department. Responsibilities: - Lead and oversee the data analysts, data scientist team, machine learning engineers, and big data specialists to implement models and systems that provide optimal results and are scalable to meet future business needs. - Serve as a subject matter expert on UPS business processes, data, and advanced analytics capabilities to define problems, data, and model requirements using proven predictive and prescriptive techniques. - Maintain a broad understanding of implementation, integration, and inter-connectivity issues with emerging technologies to develop strategies that support the creation, development, and delivery of analytic solutions aligned with business needs. - Prototype algorithms to ensure analytic results address problem statements and business requirements effectively. - Interpret and analyze large-scale datasets to uncover insights supporting the building of analytic systems and predictive models while experimenting with new and emerging techniques. - Identify and evaluate cutting-edge open-source, data science/machine learning libraries, data platforms, and vendor solutions to prioritize and plan data projects across the enterprise. - Provide thought leadership, technical guidance, and counsel for data science project teams to evaluate strategic alternatives, recommend courses of action, and design and implement solutions. - Advocate for best practices in the adoption of Cloud-AI technologies, open-source software, machine learning libraries/packages, and data science platforms to derive actionable insights empowering business decisions. - Communicate effectively with business customers and the senior leadership team with varying levels of technical knowledge, educate them about systems, and share insights and recommendations to inform business strategies. - Manage analytics projects/teams and act as a point of contact to ensure alignment of team actions and communication with stakeholders to keep projects on track with goals. Qualifications: - Ability to engage key business and executive-level stakeholders to translate business problems into high-level analytics solutions. - Extensive experience working with large-scale, complex datasets to develop machine learning, predictive, forecasting, and optimization models. - Proven track record of handling ambiguity, prioritizing needs, and delivering results in a dynamic environment. - Expertise in data management pipelines involving data extraction, analysis, and transformation using 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; utilizing Cloud-AI technologies, machine learning frameworks, and enterprise data science platforms. - Ability to explain technical concepts to non-experts, strong analytical skills, attention to detail. - Direct experience in developing analytical solutions empowering business decisions and product creation using various techniques (e.g. Supervised, Unsupervised, Deep Learning, NLP). - Excellent verbal and written communication skills with the ability to convey data through a story framework, present data-driven results to technical and non-technical audiences, and advocate technical solutions to diverse groups. - Master's Degree in a quantitative field such as mathematics, computer science, physics, economics, engineering, statistics, or equivalent job experience. Employee Type: Permanent UPS is committed to providing a workplace free of discrimination, harassment, and retaliation.,