Data Scientist (Remote)

Koniag Services Inc. a Koniag Government Services company is seeking a talented and innovative Data Scientist to support the development and implementation of advanced data science machine learning and predictive analytics solutions for our IT Call Center serving government clients. The ideal candidate is a highly analytical and technically sophisticated professional with deep expertise in data science methodologies machine learning model development and statistical analysis combined with a strong understanding of IT call center operations and service delivery environments. They bring a passion for transforming complex large-scale operational data into actionable intelligence a collaborative and solutions-oriented work ethic and the ability to work independently and effectively in a fully remote environment to deliver data science solutions that drive measurable improvements in IT Call Center performance efficiency and customer experience. Ability to obtain a government security clearance may be required to support Koniag Services Inc. and our government customers. This position is offer competitive compensation and an extraordinary benefits package including health dental and vision insurance 401K with company matching flexible spending accounts paid holidays three weeks paid time off and Description:The Data Scientist will be responsible for the design development implementation and ongoing refinement of advanced data science and machine learning solutions that support IT Call Center operational performance predictive intelligence and continuous improvement objectives. This individual will work closely with program leadership data analysts the AWS AI Practitioner the AWS Solutions Architect and government stakeholders to identify high-value data science opportunities develop and deploy analytical models and translate complex data science outputs into clear actionable insights that inform strategic and operational decision making. Principal responsibilities will include but are not limited to:Lead the end-to-end development implementation and ongoing refinement of advanced data science and machine learning solutions that address high-priority IT Call Center operational challenges and performance improvement opportunities including predictive call volume forecasting SLA risk prediction agent performance modeling and customer satisfaction with program leadership data analysts and the AWS AI Practitioner to identify prioritize and scope data science use cases that deliver the highest operational value for the IT Call Center program and government and execute comprehensive data acquisition cleaning transformation and feature engineering pipelines that prepare raw call center operational data from multiple sources for advanced analytical and machine learning modeling train validate and deploy supervised unsupervised and reinforcement learning models using industry-leading machine learning frameworks and AWS AI and ML platform services ensuring all models meet defined performance accuracy and reliability standards prior to operational and implement natural language processing (NLP) and text analytics solutions that analyze call transcripts ticket notes chat logs and customer feedback data to identify sentiment trends topic clusters emerging issues and customer experience improvement and maintain predictive analytics models that leverage historical and real-time call center operational data to forecast call volumes predict staffing requirements identify at-risk SLA performance periods and support proactive operational decision with the AWS AI Practitioner and AWS Solutions Architect to design and implement scalable cloud-native data science solution architectures on AWS leveraging Amazon SageMaker Amazon Bedrock AWS Lambda Amazon Kinesis AWS Glue and related AWS data and AI and maintain robust MLOps pipelines and practices including model versioning automated retraining workflows continuous integration and delivery for ML models and comprehensive model performance monitoring and drift detection and develop advanced data visualizations analytical reports and executive-level briefing materials that communicate complex data science findings and model outputs clearly and compellingly to non-technical program leadership and government with data analysts to ensure data science outputs are integrated effectively into operational reporting frameworks performance dashboards and decision support tools used by program leadership and call center operations rigorous model performance assessments A/B testing and experimental design analyses to evaluate the operational impact of deployed data science solutions and inform continuous model improvement all data science solution development and deployment activities comply with applicable federal security requirements data privacy regulations responsible AI governance standards AWS GovCloud policies and FedRAMP authorization technical guidance mentorship and subject matter expertise to data analysts and junior technical team members on data science methodologies machine learning concepts statistical analysis techniques and AWS AI and ML service and maintain comprehensive technical documentation for all data science solutions including model design documents feature engineering specifications training and validation results deployment procedures and operational monitoring current on emerging data science methodologies machine learning research AWS AI and ML platform updates and industry best practices proactively identifying opportunities to leverage new techniques and technologies to enhance IT Call Center operational intelligence and business development activities as needed including contributing to proposal efforts with data science capability narratives technical solution concepts analytical methodology descriptions and relevant past performance and Experience:Required:Masters 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 in a structured operational experience developing and deploying NLP predictive analytics and machine learning solutions using Python and industry-leading ML leveraging AWS AI and ML services including Amazon SageMaker Amazon Comprehend Amazon Transcribe or equivalent cloud-based ML platform working with large complex multi-source datasets in a structured analytical :Doctoral degree (Ph.D.) in Data Science Statistics Mathematics Computer Science or a related quantitative experience applying data science methodologies within a federal government contracting or AWS GovCloud supporting data science solution development for an IT call center service desk or IT managed services Certified Machine Learning Specialty certification or AWS Certified AI Practitioner working in a fully remote data science role within a government contracting Skills and Competencies:Exceptional communication skills in English both written and oral with the ability to explain complex data science concepts model outputs and analytical findings clearly and compellingly to non-technical program leadership government stakeholders and cross-functional team members in a remote work -level proficiency in Python for data science and machine learning development including extensive experience with core data science libraries such as NumPy Pandas Scikit-learn TensorFlow PyTorch Keras NLTK SpaCy and expertise in machine learning theory and practice including supervised learning unsupervised learning reinforcement learning ensemble methods neural networks deep learning architectures and model evaluation and validation proficiency in natural language processing (NLP) and text analytics techniques including tokenization named entity recognition sentiment analysis topic modeling text classification and transformer-based language model fine-tuning and proficiency in Amazon SageMaker for end-to-end ML pipeline development including data preparation model training hyperparameter tuning model deployment and automated model monitoring and proficiency in SQL and NoSQL data querying languages for extracting transforming and analyzing large-scale datasets from relational databases data warehouses and ITSM experience designing and implementing MLOps practices and pipelines including model versioning CI/CD for ML automated retraining workflows and model performance drift detection and proficiency in data visualization tools and libraries including Microsoft Power BI Tableau Matplotlib Seaborn or Plotly for communicating complex data science findings and model outputs to technical and non-technical understanding of statistical analysis concepts and methods including hypothesis testing regression analysis time series analysis Bayesian inference and experimental design as applied to operational performance ability to manage multiple complex data science initiatives simultaneously work independently with minimal supervision and deliver high-quality analytical outputs within established timelines in a remote work to obtain and maintain a government security clearance as Skills and Competencies:Active government security clearance (Secret or higher).AWS Certified Machine Learning Specialty Certified AI Practitioner Certified Solutions Architect Associate certification demonstrating cloud architecture knowledge relevant to data science solution designing and implementing data science solutions within an AWS GovCloud environment in support of federal government FedRAMP authorization and data privacy with federal IT security frameworks and compliance requirements such as NIST SP 800-53 FedRAMP FISMA and emerging federal AI governance frameworks as they relate to data science solution design and with Amazon Bedrock large language models (LLMs) and generative AI application development for intelligent automation and conversational AI use cases within a government IT service delivery with responsible AI principles AI ethics frameworks explainable AI (XAI) methodologies and algorithmic bias detection and mitigation strategies as they apply to data science solution development in a federal government with data engineering tools and platforms including AWS Glue Amazon Kinesis Amazon Redshift Apache Spark or equivalent big data processing and pipeline management with graph analytics anomaly detection or forecasting methodologies as applied to IT service delivery operational with reinforcement learning from human feedback (RLHF) and fine-tuning techniques for large language model customization in a government IT with A/B testing frameworks causal inference methodologies and experimental design for evaluating the operational impact of deployed data science of containerization and orchestration technologies such as Docker and Kubernetes as they relate to scalable ML model deployment and management in a cloud-native contributing to business development efforts including proposal writing data science capability development analytical methodology narratives and past performance Equal Employment Opportunity Policy: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 company is dedicated to seeking all qualified applicants. If you require an accommodation to navigate or to apply to a position on our website please contact Heaven Wood via e-mail at or by calling to request accommodations. Koniag Government Services (KGS) 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 Opportunity Employer/Veterans/Disabled. Shareholder Preference in accordance with Public Law 88-352