Data visualization • dallas tx
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The average salary range is between $ 91,250 and $ 150,256 year , with the average salary hovering around $ 107,500 year .
The average salary range is between $ 82,499 and $ 153,216 year , with the average salary hovering around $ 105,000 year .
v (only USC)
Location: Dallas, TX
Work Model: Hybrid
Role Overview
We are seeking an analytical and results-driven Contract Data Scientist to join our team in Dallas, TX. In this role, you will analyze large-scale datasets, build and validate predictive models, and deliver actionable insights to solve complex business problems. This position operates on a hybrid schedule, requiring 3 days onsite per week at our Dallas facility.
Key Responsibilities
Exploratory Data Analysis & Modeling: Clean, preprocess, and analyze large datasets to develop machine learning algorithms, statistical models, and predictive frameworks.
Pipeline & Feature Engineering: Design and refine robust data pipelines and feature sets to optimize model efficiency and performance.
Business Insights & Visualization: Translate complex model outputs and data analyses into intuitive visualizations, reports, and strategic recommendations for stakeholders.
Model Validation & Maintenance: Continuously test, validate, and monitor model performance in production to ensure accuracy, fairness, and reliability over time.
Cross-Functional Collaboration: Partner with data engineering, product management, and business domain teams to align data science initiatives with core organizational objectives.
Qualifications & Requirements
Experience: 3 5+ years of hands-on experience in data science, predictive modeling, and applied machine learning within a business or enterprise environment.
Technical Proficiency:
Strong programming skills in Python or R, alongside advanced SQL for complex queries and data extraction.
Practical experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn, XGBoost) and deep learning frameworks (PyTorch or TensorFlow).
Familiarity with data visualization tools (Tableau, Power BI, or Matplotlib/Seaborn).
Cloud platform experience (AWS, Azure, or GCP) for running model workflows and managing data.
Preferred Qualifications
Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Applied Mathematics, or a related quantitative field.
Prior experience working in financial services, healthcare, or corporate technology environments.
Knowledge of standard software engineering practices (Git, version control, CI/CD).
