Data Scientist

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Koniag Government Services

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 operational challenges. • Identify and prioritize 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 for multi-source call center data. • Develop, train, validate, and deploy supervised, unsupervised, and reinforcement learning models using ML frameworks and AWS AI/ML services. • Design NLP and text analytics solutions for call transcripts, ticket notes, chat logs, and customer feedback. • Develop predictive models for call volumes, staffing requirements, SLA risks, and proactive operational decisions. • Design scalable, cloud-native data science architectures on AWS. • Develop MLOps pipelines including model versioning, automated retraining, CI/CD, performance monitoring, and drift detection. • Create data visualizations, analytical reports, and executive briefings for non-technical stakeholders. • Integrate data science outputs into operational reports, dashboards, and decision-support tools. • Conduct model 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 analysts and junior technical team members. • Maintain technical documentation, deployment procedures, and monitoring runbooks. • Track emerging data science and AWS AI/ML technologies and identify improvement opportunities. • Support business development and proposal activities as needed.

🎯 Requirements

• Master's degree in Data Science, Statistics, Mathematics, Computer Science, Machine Learning, or related quantitative field required; relevant experience may substitute for an advanced degree. • 4+ years of hands-on data science experience. • 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 with AWS AI/ML services, including Amazon SageMaker, Amazon Comprehend, Amazon Transcribe, or equivalent cloud-based ML platforms. • Experience working with large, complex, multi-source datasets. • Exceptional written and oral English communication skills. • Expert-level Python proficiency, including NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, and Matplotlib. • Deep expertise in supervised, unsupervised, and reinforcement learning; ensemble methods; neural networks; deep learning; and model evaluation/validation. • Advanced NLP and text analytics proficiency, including tokenization, named entity recognition, sentiment analysis, topic modeling, text classification, and transformer model fine-tuning/deployment. • Demonstrated Amazon SageMaker proficiency for end-to-end ML pipelines, deployment, monitoring, and retraining. • Strong SQL and NoSQL proficiency. • Experience designing and implementing MLOps practices, including model versioning, ML CI/CD, automated retraining, and drift detection. • Advanced proficiency with Power BI, Tableau, Matplotlib, Seaborn, or Plotly. • Strong statistical analysis knowledge, including hypothesis testing, regression, time series analysis, Bayesian inference, and experimental design. • Ability to manage multiple complex initiatives independently and meet established timelines. • Ability to obtain and maintain a government security clearance as required. • Preferred/desired: doctoral degree, federal contracting or AWS GovCloud experience, IT call center/service desk experience, AWS certifications, federal security and AI governance familiarity, 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 paid time off • Competitive compensation

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