Data Scientist

TEGNA Inc. helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across web, mobile apps, streaming, and linear television, while also maintaining a strong global presence in India with offices in Bangalore and Chennai that support technology, product, and business operations initiatives. Together, we are building a sustainable future for local news.

About TEGNA

TEGNA Inc. (NYSE: TGNA) helps people thrive in their local communities by providing the trusted local news and services that matter most. With 64 television stations in 51 U.S. markets, TEGNA reaches more than 100 million people monthly across the web, mobile apps, streaming, and linear television. Together, we are building a sustainable future for local news.

Data Scientist

TEGNA is seeking a highly skilled, innovative, and analytical Data Scientist to lead end-to-end development of advanced models and insights across our multi-platform media ecosystem spanning TV, digital, streaming, social, and mobile. This role is central to transforming large-scale viewership, content, and sales datasets into predictive models, optimization frameworks, and actionable insights that support content strategy, personalization, audience growth, and revenue performance.

The ideal candidate is passionate about experimentation, machine learning, and building scalable data and ML solutions. You will collaborate with engineering,product, editorial, sales, and analytics teams to translate complex, ambiguous business challenges into measurable, data-driven outcomes.

What You'll Do

• Lead the full data science lifecycle: problem framing, hypothesis development, feature engineering, model development, validation, and deployment planning.
• Develop and operationalize machine learning models across forecasting, personalization, churn prediction, attribution, ranking, and content intelligence.
• Build content and audience intelligence using NLP techniques such as embeddings, semantic similarity, topic/entity modeling, summarization, and relevance scoring.
• Create sales and advertising analytics, including demand forecasting, pricing optimization, uplift modeling, and campaign effectiveness measurement.
• Conduct advanced statistical analysis, causal inference, A/B testing, uplift/experiment design, and incrementally measurement.
• Develop scalable data pipelines and training workflows in partnership with data engineering teams.
• Build unified, cross-platform KPIs and measurement frameworks to evaluate content performance and audience behavior.
• Evaluate model performance, monitor drift, establish governance, and ensure robustness and fairness of deployed models.
• Deliver clear, executive-ready insights through dashboards, automated reports, and data storytelling.
• Work closely with product, editorial, growth, and sales teams to prioritize high-impact opportunities.
• Contribute to code and design reviews, mentor teammates, and elevate analytical rigor across the organization.

What You Bring

• 5–7 years of applied Data Science experience delivering measurable business impact in media, consumer analytics, advertising, or adjacent fields.
• Strong proficiency in Python (pandas, NumPy, scikit-learn, stats models) and SQL.
• Hands-on experience building, validating, and deploying ML models(regression, classification, uplift, forecasting, clustering, recommendation,NLP).
• Strong foundation in statistics, probability, hypothesis testing, experimental design, and causal inference.
• Experience working with large-scale datasets and cloud platforms (AWS, Azure, or GCP).
• Familiarity with BI tools such as Tableau, Power BI, or Plotly for insight communication.
• Excellent analytical thinking, communication, and data storytelling skills with the ability to simplify complexity for business stakeholders.

Preferred Qualifications

• Experience with deep learning frameworks (TensorFlow, PyTorch) or advanced NLP/ML techniques.
• Exposure to big data technologies (Spark, Hadoop, Databricks).
• Experience with MLOps pipelines, model monitoring, and production ML workflows.
• Background in digital media, personalization systems, recommendation engines, or audience analytics.
• Bachelor's or master's degree in Data Science, Computer Science, Statistics,Mathematics, or a related field.

Why TEGNA

At TEGNA, our values guide everything we do. We Demand the Truth by delivering accurate, trusted information. We Work Smarter by finding better ways to solve problems and move quickly. We Do the Right Thing by holding ourselves to the highest standards. And We Win by working together to deliver results. If you're ready to grow your career in corporate communications and be part of a team that lives these values every day, we'd love to hear from you.

EEO Statement:

TEGNA Inc. is a proud equal opportunity employer. We are proud to be an equal opportunity employer, hiring and developing individuals from diverse backgrounds and experiences to add to our collaborative culture. We value and consider applications from all qualified candidates without regard to actual or perceived race, color, religion, national origin, sex, gender, age, marital status, personal appearance, sexual orientation, gender identity or expression, family responsibilities, disability, medical condition, enrollment in college or vocational school, political affiliation, military or veteran status, citizenship status, genetic information, or any other basis protected by federal, state, or local law. TEGNA will reasonably accommodate qualified individuals with disabilities in accordance with applicable law.

**Recruiting Fraud Alert:**To all candidates: your personal information and online safety are important to us. Only TEGNA Recruiters or Hiring Managers will reach out to you regarding consideration of your application or background.  Communications with TEGNA employees will either come from a TEGNA email address with a domain of tegna.com or one of our affiliate station domains.  

Recruiters or hiring managers will never request payments, ask for financial account information, or sensitive information such as social security numbers.