Data Scientist

🕒 September 9

🎸 Tennessee – Remote

🎸 Tennessee – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Koniag Government Services

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1975

🏛️ Government

🎖️ Defense

💼 Consulting

Government • Defense • Consulting

Koniag Government Services is an Alaska Native Corporation (ANC) that provides technical, professional, and operational expertise to the U. S. public sector. KGS supports Defense & Intelligence, Federal Civilian, and Health customers with enterprise solutions, professional services, and operations management, and emphasizes mission-focused outcomes, contracting speed (ANC direct awards), and strategic/technology partnerships. The company positions itself as a mission partner delivering people, technology, and program management to government customers.

📋 Description

• Lead end-to-end development, implementation, and refinement of data science and machine learning solutions for IT Call Center operations • Develop predictive call volume forecasting, SLA risk prediction, agent performance modeling, and customer satisfaction analytics • Identify, prioritize, and scope high-value data science use cases with program leadership, data analysts, AWS AI Practitioner, and government stakeholders • Design data acquisition, cleaning, transformation, and feature engineering pipelines • Develop, train, validate, and deploy supervised, unsupervised, and reinforcement learning models • Design NLP and text analytics solutions for call transcripts, ticket notes, chat logs, and customer feedback • Build predictive models for call volumes, staffing requirements, SLA risks, and proactive decision making • Design scalable cloud-native data science architectures on AWS using SageMaker, Bedrock, Lambda, Kinesis, Glue, and related services • Develop MLOps pipelines with model versioning, automated retraining, CI/CD, monitoring, and drift detection • Create data visualizations, analytical reports, and executive briefings for non-technical stakeholders • Integrate data science outputs into operational reporting, dashboards, and decision-support tools • Conduct model performance assessments, A/B testing, and experimental design analyses • Ensure compliance with federal security, privacy, responsible AI, AWS GovCloud, and FedRAMP requirements • Provide technical guidance and mentorship to data analysts and junior technical team members • Maintain technical documentation, deployment procedures, and operational monitoring runbooks • Stay current on data science, machine learning, and AWS AI/ML developments • Support business development and proposal efforts

🎯 Requirements

• Master's degree in Data Science, Statistics, Mathematics, Computer Science, Machine Learning, or a related quantitative field from an accredited college or university; relevant experience may be considered in lieu of an advanced degree • 4+ years of hands-on experience in a data science role • Experience designing, developing, and deploying machine learning models and advanced analytical solutions • Experience developing and deploying NLP, predictive analytics, and machine learning solutions using Python and industry-leading ML frameworks • Experience leveraging AWS AI and ML services, including Amazon SageMaker, Amazon Comprehend, Amazon Transcribe, or equivalent cloud-based ML platform services • Experience working with large, complex, multi-source datasets • Exceptional written and oral communication skills in English • Expert-level proficiency in Python and data science libraries including NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, and Matplotlib • Deep expertise in supervised learning, unsupervised learning, reinforcement learning, ensemble methods, neural networks, deep learning architectures, and model evaluation and validation • Advanced proficiency in NLP and text analytics, including tokenization, named entity recognition, sentiment analysis, topic modeling, text classification, and transformer-based language model fine-tuning and deployment • Demonstrated proficiency in Amazon SageMaker for end-to-end ML pipeline development • Strong proficiency in SQL and NoSQL • Experience designing and implementing MLOps practices and pipelines, including model versioning, CI/CD, automated retraining, and drift detection • Advanced proficiency in Power BI, Tableau, Matplotlib, Seaborn, or Plotly • Strong understanding of hypothesis testing, regression analysis, time series analysis, Bayesian inference, and experimental design • Ability to obtain and maintain a government security clearance as required • Ability to work independently and manage multiple complex initiatives in a remote environment

🏖️ Benefits

• Medical, dental, and vision insurance • 401(k) retirement plan • Paid time off • Paid parental leave • Life and disability insurance • Flexible spending accounts • Commuter benefits • Tuition reimbursement • Fully remote work environment