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About the Role

Koniag Services Inc. is seeking a Data Scientist to support the development and implementation of advanced data science, machine learning, and predictive analytics solutions for their IT Call Center serving government clients. The role requires a highly analytical professional with expertise in data science methodologies, machine learning, and statistical analysis, combined with an understanding of IT call center operations. The candidate should be passionate about transforming data into actionable intelligence and capable of working independently in a fully remote environment to drive improvements in IT Call Center performance, efficiency, and customer experience. Ability to obtain a government security clearance may be required.

Responsibilities

Lead the end-to-end development, implementation, and ongoing refinement of advanced data science and machine learning solutions addressing IT Call Center operational challenges and performance improvement opportunities.
Collaborate with program leadership, data analysts, and the AWS AI Practitioner to identify, prioritize, and scope data science use cases.
Design and execute data acquisition, cleaning, transformation, and feature engineering pipelines.
Develop, train, validate, and deploy supervised, unsupervised, and reinforcement learning models using industry-leading ML frameworks and AWS AI/ML services.
Design and implement NLP and text analytics solutions to analyze call transcripts, ticket notes, chat logs, and customer feedback.
Develop and maintain predictive analytics models to forecast call volumes, predict staffing requirements, and identify at-risk SLA performance periods.
Partner with AWS AI Practitioner and Solutions Architect to design and implement scalable, cloud-native data science solution architectures on AWS.
Develop and maintain MLOps pipelines and practices including model versioning, automated retraining, CI/CD for ML, and model performance monitoring.
Design and develop advanced data visualizations, analytical reports, and executive-level briefing materials.
Collaborate with data analysts to integrate data science outputs into operational reporting frameworks and dashboards.
Conduct model performance assessments, A/B testing, and experimental design analyses.
Ensure all data science activities comply with federal security requirements, data privacy regulations, responsible AI governance, AWS GovCloud policies, and FedRAMP authorization.
Provide technical guidance, mentorship, and subject matter expertise to data analysts and junior technical team members.
Develop and maintain comprehensive technical documentation for all data science solutions.
Stay current on emerging data science methodologies, machine learning research, and AWS AI/ML platform updates.
Support business development activities, including contributing to 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, with demonstrated experience designing, developing, and deploying machine learning models and advanced analytical solutions.
Demonstrated 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 in a structured analytical environment.
Ability to obtain and maintain a government security clearance as required.

Skills

Exceptional communication skills (written and oral) for explaining complex data science concepts to non-technical audiences.
Expert-level proficiency in Python for data science and machine learning development.
Extensive experience with core data science libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Keras, NLTK, SpaCy, and Matplotlib.
Deep expertise in machine learning theory and practice (supervised, unsupervised, reinforcement learning, ensemble methods, neural networks, deep learning).
Advanced proficiency in natural language processing (NLP) and text analytics techniques.
Demonstrated proficiency in Amazon SageMaker for end-to-end ML pipeline development.
Strong proficiency in SQL and NoSQL data querying languages.
Demonstrated experience designing and implementing MLOps practices and pipelines.
Advanced proficiency in data visualization tools and libraries (Microsoft Power BI, Tableau, Matplotlib, Seaborn, Plotly).
Strong understanding of statistical analysis concepts and methods.
Demonstrated ability to manage multiple complex data science initiatives simultaneously and work independently.
Active government security clearance (Secret or higher) is desired.
AWS Certified Machine Learning – Specialty certification is desired.
AWS Certified AI Practitioner certification is desired.
AWS Certified Solutions Architect – Associate certification is desired.
Experience designing and implementing data science solutions within an AWS GovCloud environment is desired.
Familiarity with federal IT security frameworks and compliance requirements (NIST SP 800-53, FedRAMP, FISMA) is desired.
Experience with Amazon Bedrock, large language models (LLMs), and generative AI is desired.
Familiarity with responsible AI principles, AI ethics frameworks, and explainable AI (XAI) is desired.
Experience with data engineering tools and platforms (AWS Glue, Amazon Kinesis, Amazon Redshift, Apache Spark) is desired.
Experience with graph analytics, anomaly detection, or forecasting methodologies is desired.
Familiarity with reinforcement learning from human feedback (RLHF) and fine-tuning techniques for LLMs is desired.
Experience with A/B testing frameworks, causal inference methodologies, and experimental design is desired.
Knowledge of containerization and orchestration technologies (Docker, Kubernetes) is desired.
Experience contributing to business development efforts including proposal writing is desired.

Location

Remote

Work Type

Remote
Full-time

Experience Level

4+ years of hands-on experience in a data science role

Education Level

Master's degree in Data Science, Statistics, Mathematics, Computer Science, Machine Learning, or a related quantitative field
Doctoral degree (Ph.D.) in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative field (Preferred)

Benefits

Medical insurance
Dental insurance
Vision insurance
401(k) retirement plan
Paid time off
Paid parental leave
Life insurance
Disability insurance
Flexible spending accounts
Commuter benefits
Tuition reimbursement

About the Company

Koniag Services Inc., a Koniag Government Services company, is an Alaska Native Owned corporation supporting the values and traditions of our native communities through an agile employee and corporate culture that delivers Enterprise Solutions, Professional Services and Operational Management to Federal Government Agencies.
As a wholly owned subsidiary of Koniag, we apply our proven commercial solutions to a deep knowledge of Defense and Civilian missions to provide forward leaning technical, professional, and operational solutions.
KGS enables successful mission outcomes for our customers through solution-oriented business partnerships and a commitment to exceptional service delivery.
We ensure long-term success with a continuous improvement approach while balancing the collective interests of our customers, employees, and native communities.
For more information, please visit www.koniag-gs.com.

Equal Opportunity

The company is an equal opportunity employer. The company shall not discriminate against any employee or applicant because of race, color, religion, creed, ethnicity, sex, sexual orientation, gender or gender identity (except where gender is a bona fide occupational qualification), national origin or ancestry, age, disability, citizenship, military/veteran status, marital status, genetic information or any other characteristic protected by applicable federal, state, or local law.
We are committed to equal employment opportunity in all decisions related to employment, promotion, wages, benefits, and all other privileges, terms, and conditions of employment.
The company is dedicated to seeking all qualified applicants.
Equal Opportunity Employer/Veterans/Disabled.
Shareholder Preference in accordance with Public Law 88-352