About the Role

TEGNA is seeking a highly skilled, cutting-edge, and analytical Data Scientist to lead the end-to-end development of advanced models and insights across a 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
- 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
- Deployment planning

- Develop and operationalize ML models across:

- Forecasting
- Personalization
- Churn prediction
- Attribution
- Ranking
- Content intelligence

- Build content and audience intelligence using NLP techniques:

- Embeddings
- Semantic similarity
- Topic/entity modeling
- Summarization
- Relevance scoring

- Create sales and advertising analytics:

- Demand forecasting
- Pricing optimization
- Uplift modeling
- Campaign effectiveness measurement

- Conduct advanced statistical analysis:

- Causal inference
- A/B testing
- Uplift/experiment design
- Incrementality measurement

- Develop scalable data pipelines and training workflows with data engineering teams
- Build unified,



cross-platform KPIs and measurement frameworks
- Monitor and improve model performance:

- Drift detection
- Governance
- Robustness and fairness

- Deliver executive-ready insights via:

- Dashboards
- Automated reports
- Data storytelling

- Collaborate with product, editorial, growth, and sales teams to prioritize opportunities
- Contribute to code/design reviews and mentor team members

What You Bring

- 5–7 years of applied Data Science experience delivering measurable business impact (media, consumer analytics, advertising, or related domains)
- Strong proficiency in:
- Python (pandas, NumPy, scikit-learn, statsmodels)
- SQL

- Hands-on experience with ML models:

- Regression
- Classification
- Uplift
- Forecasting
- Clustering
- Recommendation systems
- NLP

- Strong foundation in:

- Statistics
- Probability
- Hypothesis testing
- Experimental design
- Causal inference

- Deep understanding of:

- Vector embeddings
- Vectorization techniques

- Experience with:

- Large-scale datasets
- Cloud platforms (AWS, Azure, GCP)

- Familiarity with BI tools:

- Tableau
- Power BI
- Plotly

- Strong communication and data storytelling skills

Preferred Qualifications

- Experience with deep learning frameworks:
- TensorFlow
- PyTorch

- Exposure to big data technologies:

- Spark
- Hadoop
- Databricks

- Experience with:

- MLOps pipelines
- Model monitoring
- Production ML workflows

- Background in:

- Digital media
- Personalization systems
- Recommendation engines
- Audience analytics

- Bachelor’s or Master’s degree in:

- Data Science
- Computer Science
- Statistics
- Related fields

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