Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.
Job Description
Senior Data Scientist Prescient Edge Federal - 4.1 Doral, FL Job Details Full-time 15 hours ago Benefits Health insurance Dental insurance Tuition reimbursement On-the-job training Vision insurance Retirement plan Qualifications AI models Data preprocessing Predictive modeling analysis AI platforms (beyond public GPTs) Computational framework Production systems Machine intelligence Model deployment Supervised learning Geospatial analysis Predictive analytics projects Unsupervised learning Machine learning libraries Machine learning frameworks Feature engineering
Full Job Description Job Description:
Prescient Edge is seeking a Senior Data Scientist to support a federal government client. Please note that the availability of this position is contingent upon.
Benefits:
At Prescient Edge, we believe that acting with integrity and serving our employees is the key to everyone's success. To that end, we provide employees with a best-in-class benefits package that includes: A competitive salary with performance bonus opportunities. Comprehensive healthcare benefits, including medical, vision, dental, and orthodontia coverage. A substantial retirement plan with no vesting schedule. Career development opportunities, including on-the-job training, tuition reimbursement, and networking. A positive work environment where employees are respected, supported, and engaged.
Description:
Design and implement advanced ML models and statistical methods to optimize forecasting, risk assessment, and decision-making processes. Conduct data provenance tracking, ensuring documentation of sources, transformations, and lineage for compliance with governance policies. Submit the Data Provenance & Lineage Report, summarizing transformation workflows, feature engineering processes, and audit compliance.
Job Requirements:
Experience:
Possess the knowledge and capability to develop advanced machine learning models and optimize analytic workflows for predictive and prescriptive intelligence. Personnel must be proficient in deep learning, supervised and unsupervised learning techniques, data wrangling, and feature engineering. Experience with data provenance tracking, model explainability, and bias mitigation in AI/ML applications is required. Personnel must be able to translate operational challenges into analytic solutions, ensuring integration of structured, unstructured, and geospatial data. Personnel must have demonstrated experience in building and validating AI/ML models using Python, TensorFlow, PyTorch, or Scikit-learn, integrating models into production environments, and optimizing performance for real-time analytics. Experience with Databricks, Apache Spark, or similar distributed data processing frameworks is required. Personnel must also have experience working with geospatial datasets and integrating AI/ML solutions into mission-critical applications.
Education:
A Master's degree in Data Science, Machine Learning, Statistics, or a related field, or nine (9) years of equivalent experience in AI/ML model development and deployment. Desirable but not required certifications include
Google Professional Machine Learning Engineer, Microsoft Certified:
Azure Data Scientist Associate, or TensorFlow Developer Certification.