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Senior Data Scientist
| Company | AT&T |
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| Location | Dallas, TX, USA |
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| Salary | $148200 – $222400 |
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| Type | Full-Time |
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| Degrees | Master’s |
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| Experience Level | Senior |
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Requirements
- Proficiency in at least one data science language (Python, R, Scala, etc.)
- Expertise with modern ML packages and libraries (Spark, SciKitLearn, Pandas, PyTorch, TidyVerse, Tensorflow, Keras, Shiny, and/or AutoML tools)
- Highly proficient in the full AI workflow such as data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining
- Well-versed in Interactive Development Environments (IDEs) such as Databricks Workspaces or Visual Studio Code
- Proficiency in algorithm categories such as Supervised Learning, Unsupervised Learning, Optimization Algorithms, Deep Learning, AI-Computer Vision, Natural Language Processing, Deep Reinforcement Learning, Search Algorithms, and AI- Knowledge Graphs
- Master’s degree (MS/MA) required from an accredited University in a Quantitative field of study such as Data Science, Math, Statistics, Engineering or Physics
- 3+ years of related experience
Responsibilities
- Collect data from various structured and unstructured sources and ensure its quality for analysis through cleaning and preprocessing
- Design, build, and analyze large and complex data sets while thinking strategically about data use and data design
- Create relevant features and conduct exploratory data analysis
- Code solutions following typical workflow; data extraction, cleansing, feature engineering, exploratory data analysis, model selection/creation, hyper-parameter tuning, model interpretation, model retraining, business process and/or system implementations, high level proof of concept and trials, visualization, deployment to production, post deployment ML ops monitoring/diagnosis/resolutions
- Build, evaluate, and optimize machine learning models through hyperparameter tuning
- Implement models into production, continuously monitor their performance, and ensure they remain explainable and reliable to minimize model decay
- Create visualizations and reports for stakeholders while working closely with cross-functional teams to align efforts with business objectives
- Develop and implement generative AI models, focusing on creating new content or augmenting existing data
Preferred Qualifications
No preferred qualifications provided.
