Senior Engineer-Data Science

You want more out of a career. A place to share your ideas freely — even if they’re daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love — driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together — lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the V Team Life.

What You’ll Be Doing…

Commercial Data & Analytics Hub is part of the Verizon Global Services (VGS) organization. In this hub, you will be part of an advanced analytics team tackling supply chain and business operations problems. The team’s goal is to provide actionable insights that drive business value. Our team leverages big data and tools like statistical analysis, machine learning algorithms, optimization methods, operations research techniques, and related analytical tools. For our team, developing a thorough understanding of the business context is absolutely critical to success.

As part of this team, you must possess a strong understanding of data structures, mathematical modeling, and machine learning methodologies. You will need to develop a thorough understanding of the business context relevant to each project you support. You will apply your technical expertise and business knowledge to extract meaningful insights from complex datasets. You will then need to communicate your findings to stakeholders and influence strategic decision-making.

The ideal team member is someone who can help us and our business partners solve supply chain and operations problems from end-to-end through the stages of problem definition, hypothesis development, data preparation, model selection and training, and insight generation.

• Deeply understand business requirements and translate them into well-defined analytical problems, identifying the most appropriate statistical techniques and modeling approaches to deliver impactful solutions.
• Expertly manipulate and prepare data for modeling, leveraging your knowledge of data structures, transformation techniques, and feature engineering to optimize model performance.
• Lead the design, development, and validation of sophisticated statistical models and machine learning algorithms to address complex business challenges and drive strategic decision-making.
• Develop and implement rigorous model validation frameworks to ensure the accuracy, reliability, and generalizability of your models, adhering to best practices in statistical modeling and machine learning.
• Clearly and effectively communicate complex statistical concepts and model results to both technical and non-technical audiences, translating your findings into actionable insights for stakeholders.

What We’re Looking For…

You will need to Have:

• Bachelor’s degree or four or more years of work experience
• Four or more years of relevant work experience
• A deep understanding of various machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, and time series analysis
• Advanced programming skills in Python or R with deep familiarity with relevant machine learning and data manipulation libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy)
• Proficiency in SQL, including experience with large datasets and distributed computing environments.
• Ability to collaborate effectively across teams for data discovery and validation
• Excellent communication and presentation skills, with the ability to clearly articulate complex technical concepts to both technical and non-technical audiences.

Even better if you have one or more of the following:

• Experience in maintaining repositories in Git
• Experience with Alteryx.
• Experience with dashboards creation using Tableau/QLIK/Looker
• Expertise in advanced statistical modeling techniques, such as Bayesian inference or causal inference.
• Experience with supply chain and business operations processes
• Practical experience or strong theoretical understanding of large language models (LLMs) and their applications in a business context.
• An understanding of the ethical considerations and potential biases associated with generative AI, and strategies for responsible development and deployment.
• Contributions to open-source projects or publications in relevant data science or machine learning conferences.
• Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and deploying machine learning models at scale using platforms like Domino Data Lab or Vertex AI
• Experience in applying statistical ideas and methods to data sets to answer business problems.
• Excellent interpersonal, verbal and written communication skills.

If Verizon and this role sound like a fit for you, we encourage you to apply even if you don’t meet every “even better” qualification listed above.

Where you’ll be working

In this hybrid role, you’ll have a defined work location that includes work from home and assigned office days set by your manager.

Scheduled Weekly Hours

40

Diversity and Inclusion

We’re proud to be an equal opportunity employer. At Verizon, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more.