Data Scientist

This is a fully remote position, open to applicants in Tennessee.

📋 Description

• Oversee the complete development, implementation, and enhancement of data science and machine learning solutions to address operational challenges within the IT Call Center.

• Collaborate with program leadership, data analysts, AWS AI Practitioners, and government stakeholders to identify and prioritize high-impact data science use cases.

• Create pipelines for data acquisition, cleaning, transformation, and feature engineering that leverage multi-source call center data.

• Build, train, validate, and deploy supervised, unsupervised, and reinforcement learning models utilizing ML frameworks and AWS AI/ML services.

• Develop NLP and text analytics solutions for call transcripts, ticket notes, chat logs, and customer feedback.

• Construct predictive models to forecast call volumes, staffing needs, SLA risks, and to inform proactive operational decisions.

• Design scalable, cloud-native data science architectures on AWS.

• Create MLOps pipelines that include model versioning, automated retraining, CI/CD, performance monitoring, and drift detection.

• Produce data visualizations, analytical reports, and executive briefings tailored for non-technical stakeholders.

• Integrate data science outputs into operational reports, dashboards, and decision-support systems.

• Perform model evaluations, A/B testing, and experimental design analyses.

• Ensure adherence to federal security, privacy, responsible AI, AWS GovCloud, and FedRAMP standards.

• Offer technical guidance and mentorship to analysts and junior technical team members.

• Maintain comprehensive technical documentation, deployment procedures, and monitoring runbooks.

• Monitor emerging data science and AWS AI/ML technologies to identify opportunities for improvement.

• Assist with business development and proposal efforts as required.

⛳️ Requirements

• A Master's degree in Data Science, Statistics, Mathematics, Computer Science, Machine Learning, or a related quantitative field is required; relevant experience can substitute for an advanced degree.

• A minimum of 4 years of practical data science experience.

• Proven experience in designing, developing, and deploying machine learning models along with advanced analytical solutions.

• Proficient in developing and implementing NLP, predictive analytics, and machine learning solutions using Python and leading industry ML frameworks.

• Familiarity with AWS AI/ML services, such as Amazon SageMaker, Amazon Comprehend, Amazon Transcribe, or similar cloud-based ML platforms.

• Experience handling large, complex, multi-source datasets.

• Outstanding written and verbal communication skills in English.

• Advanced level proficiency in Python, including libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, and Matplotlib.

• Extensive knowledge in supervised, unsupervised, and reinforcement learning; ensemble methods; neural networks; deep learning; and model evaluation/validation.

• Proficient in advanced NLP and text analytics techniques, including tokenization, named entity recognition, sentiment analysis, topic modeling, text classification, and transformer model fine-tuning/deployment.

• Demonstrated proficiency in Amazon SageMaker for managing end-to-end ML pipelines, deployment, monitoring, and retraining.

• Strong skills in SQL and NoSQL databases.

• Experience in designing and implementing MLOps practices, such as model versioning, ML CI/CD, automated retraining, and drift detection.

• Advanced capabilities with Power BI, Tableau, Matplotlib, Seaborn, or Plotly.

• Strong understanding of statistical analysis, including hypothesis testing, regression, time series analysis, Bayesian inference, and experimental design.

• Ability to independently manage multiple complex projects and adhere to established deadlines.

• Capability to obtain and maintain a government security clearance as required.

• Preferred qualifications include: a doctoral degree, experience with federal contracting or AWS GovCloud, IT call center/service desk background, AWS certifications, familiarity with federal security and AI governance, knowledge of Bedrock/LLM/generative AI, data engineering, graph analytics, anomaly detection, forecasting, RLHF, causal inference, Docker, Kubernetes, and proposal writing experience.

🏝️ Benefits

• Health, dental, and vision insurance

• 401K with company matching

• Flexible spending accounts

• Paid holidays

• Three weeks of paid time off

• Competitive compensation