Principal Engineer Data Science

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What you'll be doing...

The Principal Engineer plays a pivotal role in driving advanced analytics initiatives within our newly established Value Reporting & Analytics organization. This leader will oversee a team of skilled offshore data scientists tasked with developing and implementing sophisticated analytical models, predictive analytics, and data-driven solutions that enhance customer experiences, optimize marketing strategies, and improve operational efficiency.

This role will aid in establishing unified metrics of success across all value brands, ensuring that strategic decisions are supported by accurate and comprehensive data. The Principal Engineer will collaborate with cross-functional stakeholders in sales operations, marketing, global technology services (GTS), and finance to advance key strategic initiatives.

In addition to delivering insightful analytical results, the Principal Engineer will lead efforts to standardize data collection and reporting processes across diverse systems and tools, tackling the challenges of siloed data within each respective Value brand. By defining, refining, and mining data, this leader will establish clear metrics and methodologies for data integrity, aiding in the creation of a single source of truth that enhances decision-making across the entire organization.

Responsibilities include:

• Driving the development and implementation of advanced analytics models to support strategic decision-making and optimize the business performance of the Value brands

• Partnering with GTS and data engineering teams to ensure the integrity, accessibility, and scalability of data sources and analytics platforms, while ensuring one source of truth for all Value brands.

• Overseeing the creation, testing, and maintenance of predictive and prescriptive analytics models (e.g., churn prediction, customer segmentation, revenue forecasting).

• Identifying strengths and weaknesses in financial performance and recommend optimizations.

• Using SQL/Teradata, design up-front statistical analytics plans, ensuring the ability to quantify gains and test/learn new variances of existing strategies.

• Building, automating, and monitoring data warehouse processes via SQL queries that qualify customers for these strategies.

• Deciphering performance across a variety of metrics: i.e. KPIs, LNP, Segmentation, Propensity, etc. to uncover new opportunities for growth and revenue from the Verizon base.

• Presenting recommendations for strategy improvements and provide strong justifying evidence to defend these recommendations.

• Gaining alignment across work groups and implement these changes.

What we're looking for...

This role requires a unique blend of technical expertise in data science, strategic vision, and collaborative leadership-critical for navigating the complexities of our ecosystem and driving organizational success. The ideal candidate will possess a strong background in data analysis, machine learning, and analytics strategy, along with proven experience in leading high-performing teams.

You'll need to have:

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field; or six or more years of work experience.

• Six or more years of relevant experience required, demonstrated through one or a combination of work and/or military experience, or specialized training.

• Six or more years of experience in data science, advanced analytics, data science, business intelligence, marketing analytics, and/or financial analysis

• Proficient in programming languages (e.g., Python, R), data manipulation (e.g., SQL), and statistical analysis

• Demonstrated experience in developing and deploying predictive analytics models and frameworks that drive business impact.

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

• Strong understanding of the prepaid telecommunications industry and associated analytics needs, including regulatory issues, pricing strategies, and customer behavior

• Experience managing multiple projects simultaneously, with strong organizational and analytical skills.

• Ability to create compelling narratives to influence decision-makers

• Proficiency of various machine learning algorithms and their suitability for Value prepaid data analysis

• Understanding of telecom networks and how to analyze performance data to optimize service delivery

• Familiarity with tools such as Hadoop, Spark, and Cloud platforms, e.g. Google Cloud) for handling large datasets

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.

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