Job Description

When you join Verizon

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…

As a Consultant (Data Science) you will own and perform specific analytics tasks and lead and drive end to end solutions for AI/ML use cases with guidance from lead / manager.

• Building and deploying Statistical/Machine Learning/Deep Learning based models according to business requirements

• Contributing to model design including algorithm selection, feature requirements, model and use case validation

• Analyzing structured and unstructured data using data mining/statistical/machine learning/deep learning tools, Data visualization, Digital/Web analytics tools and techniques and storytelling.

• Performing tasks related to Operationalization - eg. wrapper script, REST service, Trigger, Monitoring etc.

• Preparing all the supporting documents and reports.

• Guiding other members in the team on technical aspects as needed.

What we’re looking for:

You have strong analytical skills, and are eager to work in a collaborative environment with global teams to drive ML application in business problems, develop end to end analytical solutions and communicate insights and findings to leadership. You work independently and are always willing to learn new technologies. You thrive in a dynamic environment and are able to interact with various partners and multi-functional teams to implement data science driven business solutions.

You'll need to have:

• Bachelor's degree or four or more years of work experience.

• Four or more years of relevant work experience.

• Experience in multi-modal modeling, including experience with frameworks such as TensorFlow, PyTorch, or Keras.

• Proficiency in machine learning, deep learning, and statistical modeling techniques.

• Solid programming skills in Python or other relevant languages.

• Experience with natural language processing, computer vision, or audio processing is highly desirable.

• Familiarity with cognitive AI techniques, such as reasoning, knowledge graphs, or symbolic reasoning.

• Proven track record of designing and implementing successful multi-modal models and algorithms, demonstrated through publications, projects, or industry experience.

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

• Advanced degree in Computer Science, Data Science, Machine Learning, or a related field.

• Experience working on cloud platforms like GCP.

• Experience in building AI models for telecom businesses.

• Strong problem-solving skills and ability to work on complex, open-ended research problems.

• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams.

• Self-motivated, proactive, and able to manage multiple tasks and priorities in a fast-paced environment.

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

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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.