Role Description Five Rivers Analytics is seeking a skilled and mission‑driven Data Engineer to support the United States Marine Corps (USMC) Logistics Data Systems Program under NIWC Atlantic. The ideal candidate will play a critical role in designing, building, and maintaining data pipelines and analytics solutions that enhance logistics readiness, operational visibility, and data‑driven decision‑making across the Marine Corps enterprise. Responsibilities: - Design, develop, and maintain scalable data pipelines to ingest, transform, and curate logistics, maintenance, and supply‑chain data from multiple USMC systems. - Implement robust ETL/ELT workflows to support analytics, reporting, and data warehousing initiatives. - Collaborate with data analysts, software engineers, and system integrators to ensure high‑quality data delivery for operational and strategic use cases. - Optimize database performance, manage data models, and ensure data accessibility and consistency across environments. - Work with NIWC Atlantic and USMC stakeholders to translate logistics data requirements into technical solutions. - Integrate data from authoritative USMC logistics systems such as GCSS‑MC, TLS, and other readiness and sustainment datasets. - Ensure compliance with DoD cybersecurity, RMF, and data governance standards when designing and deploying solutions. - Support the development of dashboards, APIs, and analytics tools that improve supply‑chain visibility and asset readiness. - Troubleshoot data issues, perform root‑cause analysis, and implement corrective actions to maintain data integrity. Qualifications - Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or a related field (or equivalent experience). - Hands‑on experience with SQL, relational databases, and data modeling. - Proficiency with modern ETL/ELT tools and data pipeline technologies (such as Python, Airflow, Spark, or similar). - Experience with cloud environments (AWS, Azure, or DoD‑specific cloud platforms). - Ability to work within Agile teams and collaborate with cross‑functional technical and government stakeholders. - Strong understanding of data quality, integrity, and governance principles. - Active DoD Secret Clearance (or ability to obtain and maintain one). Requirements - Experience supporting DoD, USMC, or logistics/sustainment data systems. - Familiarity with NIWC Atlantic processes, environments, and program expectations. - Exposure to GCSS‑MC, logistics readiness systems, or maintenance/supply‑chain data environments. - Experience with containerization, CI/CD pipelines, and DevSecOps concepts. - Knowledge of RMF, cybersecurity best practices, and secure data engineering approaches. Benefits - The company offers a comprehensive benefits program, including medical, dental, vision, life insurance, 401(k) and a range of other voluntary benefits. - Paid Time Off (PTO) is offered to regular full-time and part-time employees. Company Description Five Rivers Analytics (FRA), an Akima company, is not just another federal IT contractor. As an Alaska Native Corporation (ANC), our mission and purpose extend beyond our exciting federal projects as we support our shareholder communities in Alaska. - At FRA, the work you do every day makes a difference in the lives of our 15,000 Iñupiat shareholders, a group of Alaska natives from one of the most remote and harshest environments in the United States. - For our shareholders, FRA provides support and employment opportunities and contributes to the survival of a culture that has thrived above the Arctic Circle for more than 10,000 years. - For our government customers, FRA delivers streamlined operations in support of an increasingly fast-paced, complex, and dynamic digital environment. - As a FRA employee, you will be surrounded by a challenging, yet supportive work environment that is committed to innovation and diversity, two of our most important values. - You will also have access to our comprehensive benefits and competitive pay in addition to growth opportunities and excellent retirement options.

Role Description We are seeking a Senior Data Scientist to play a key role in delivering advanced analytics across client engagements within our Advanced Analytics team. This role is responsible for leading complex analytical workstreams, applying robust statistical methodologies, and contributing to high-quality, actionable insights. You will partner closely with analytics, research, and client teams to translate business questions into analytical approaches and deliver outputs that inform decision-making. This is an ideal opportunity for an experienced data scientist looking to expand their ownership of projects while continuing to deepen technical expertise in market research methodologies. The Salary Range for this position is $100,000 - $115,000. If this is not the right level for you, please check out our other postings. For this remote position, must be based in the United States. What You’ll Do: - Lead Advanced Quantitative Analysis - Design and execute statistical models, including: - Regression and multivariate analysis - Segmentation and clustering techniques - Choice modeling and conjoint analysis - Lead model estimation, validation, and interpretation for assigned workstreams - Ensure analytical approaches are rigorous, scalable, and aligned to study objectives - Drive Analytical Workstreams on Client Engagements - Translate business and research questions into structured analytical approaches - Lead key components of analysis within client projects, partnering with senior team members on overall strategy - Contribute to development of insights that are clear, actionable, and aligned to client needs - Work with Complex Market Research Data - Prepare, transform, and validate survey and panel datasets - Apply data quality checks, weighting, and standard processing techniques - Develop efficient workflows to support repeatable and scalable analysis - Collaborate Across Teams - Partner with research and client teams to align on study objectives and outputs - Translate analytical findings into clear summaries for internal and client-facing use - Support development of deliverables and presentations that communicate insights effectively - Contribute to Best Practices and Team Growth - Follow and help reinforce standards for coding, documentation, and reproducibility - Participate in knowledge sharing and continuous improvement efforts - Provide informal guidance to junior team members as appropriate - Apply and Advance Synthetic Data Capabilities - Apply synthetic data techniques to support research design, modeling, and data augmentation - Ensure appropriate use of synthetic datasets while maintaining analytical integrity and validity - Contribute to expanding team capabilities and best practices in synthetic data applications Qualifications - 4–8 years of experience in data science, applied statistics, or market research analytics - Strong proficiency in R or Python for data analysis and modeling - Demonstrated experience with: - Regression and multivariate analysis - Segmentation techniques (e.g., clustering) - Choice modeling / conjoint analysis - Application of synthetic data in analytics workflows or research contexts - Experience working with survey, panel, or behavioral datasets - Strong problem-solving skills and attention to detail - Ability to clearly communicate analytical findings to non-technical audiences Preferred Qualifications - Experience in market research, consulting, or client-facing analytics environments - Familiarity with experimental design or causal inference methodologies - Experience contributing to multi-phase or complex client engagements - Have experience or exposure to algorithms capable of generating synthetic data Benefits - Medical, Dental, and Vision Insurance - Large carriers on a national level (domestic partner coverage included) - 401k with Company Match - Flexible PTO - Feel no guilt in taking off a minimum of 3 weeks of “real” vacation time - Paid Parental leave: 8 weeks - Paid Sick Leave: up to 8 weeks - 12 Paid Company Holidays - Hybrid/Virtual Work - Virtual-first workforce with employees in most states - Salary range for this role is $100,000 - $115,000 Equal Opportunity Employer All qualified applicants will receive consideration for employment without regard to race, color, sex, sexual orientation, gender identity, religion, national origin, disability, veteran status, age, marital status, pregnancy, genetic information, or other legally protected status.

Job Description Are You Ready to Make It Happen at Mondelēz International? Join our Mission to Lead the Future of Snacking. Make It With Pride. You will help our business react to changing business conditions with excellent data analysis. You will define the requirements, perform the analysis and identify patterns in large amounts of data. Key responsibilities: - Support o9 model build phase covering EDA, Feature Engg, Experimentation, slicing strategy, parameter tuning and reports review in coordination with RDS - Support resolving model input data defects in coordination with Data Science Leads, BU DP Champions and Data Stewards - Perform experiments supporting value to o9 model building on o9 experiment zone/tenant - Participate in o9 Data Science trainings and upskilling plan - Support Achilles project to harmonize the forecast granularity, driver ingestion and experimentation - Support during integration testing and user testing for specific business units in scope - Support BU wise Data Qulaity Imporvement track - Build long term sustainable plan for AI/ML Model runs for the specific BU in scope More about this role Technical requirements: - Experience in any Data Science language like Python, Spark/Pyspark, SparkML, R, o9 - Experience with Cloud solutions (GCP), Bigquery, Uniy Catalog and deployment of data science models in production environment. - Knowledge and experience in data science cloud platforms like o9 solutions, Databricks or similar. - Knowledge of analytical techniques in statistical modelling, machine learning with exposure to forecasting domain especially driver-based forecasting - Basic understanding of supply chain processes - Should be able to articulate data science outcome into business understandable language. - Experience developing and deploying high standard Statistical and/or machine learning solution. - Agile project management experience, good stakeholder management, vendor management skills - 6+ years of experience in data science or advance analytics roles - Bachelors or masters degree in Engineering, Statistics, Data science, data analytics or relevant fields No Relocation support available Business Unit Summary At Mondelēz International, our purpose is to empower people to snack right by offering the right snack, for the right moment, made the right way. That means delivering a broad range of delicious, high-quality snacks that nourish life's moments, made with sustainable ingredients and packaging that consumers can feel good about. We have a rich portfolio of strong brands globally and locally including many household names such as Oreo, belVita and LU biscuits; Cadbury Dairy Milk, Milka and Toblerone chocolate; Sour Patch Kids candy and Trident gum. We are proud to hold the top position globally in biscuits, chocolate and candy and the second top position in gum. Our 80,000 makers and bakers are located in more than 80 countries and we sell our products in over 150 countries around the world. Our people are energized for growth and critical to us living our purpose and values. We are a diverse community that can make things happen-and happen fast. Mondelēz International is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, gender, sexual orientation or preference, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. Job Type Regular Data Science Analytics & Data Science

• Designing and implementing state of the art Large Language Model (LLM) based agents • Using advanced Generative AI techniques deriving actionable insights from unstructured text data • Predicting client interest basis their digital footprint • Leverage statistical and machine learning techniques to extract actionable insights from client retention data • Develop customer churn prediction models • Build tools to process structured and unstructured data