Manager - Data Science & Machine Learning - Flex Location

UPS•Parsippany, NJ

1d•Hybrid

About The Position

We will consider candidates in Mahwah, NJ, Parsippany, NJ and Atlanta, GA. This is a Hybrid position. You will be required to work from the office 3 days a week. JOB SUMMARY This position manages and advocates for various data science teams on best practices around the development and implementation of advance analytic systems and predictive and prescriptive models. This position manages the daily activities of the team responsible for identifying business trends and problems through big data analysis. This position oversees the interpretation of results from multiple sources using a variety of techniques, ranging from simple data aggregation via statistical analysis to complex data mining. This position manages and 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 manages 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.

Requirements

Ability to engage key business and executive-level stakeholders to translate business problems to high level analytics solution approach.
Experience in management of business processes, data, and advanced analytics capabilities to scope problems, data and model requirements, and proven predictive and prescriptive techniques.
Oversee the development of Machine Learning (ML), Artificial Intelligence (AI) ,GenAI and Agentic applications, from initial research and prototyping to deployment and scaling. This often involves leveraging technologies like large language models (LLMs) and natural language processing (NLP).
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) and/or statistical/mathematical software
Provide a strong understanding of AI and machine learning concepts, including evaluating models, optimizing infrastructure, and ensuring solutions are scalable, reliable, and meet performance requirements.
Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams as well as 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, and 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.

Responsibilities

Manages 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.
Maintains broad understanding of implementation, integration, and inter-connectivity issues with emerging technologies to define and manage strategies that support the creation, development and delivery of analytic solutions that meet business needs.
Manages, plans, and champions the execution of broad advanced analytics initiatives aimed at delivering value to internal and external stakeholders.
Plans, develops, and prototypes algorithms to ensure analytic results satisfy problem statements and business needs.
Leads the evaluation and analysis of 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.
Serves as a management liaison 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.
Communicates verbally and in writing to business customers and senior leadership team with various levels of technical knowledge, and educates them about our systems, as well as sharing insights and recommendations that can inform business strategies.
Adapts available Cloud-AI technologies and machine learning frameworks with or without the use of enterprise data science platforms.