Mission Box Solutions
Data Scientist
Location:
HYBRID – Ashburn, VA, United States Data Scientist We are seeking a Data Scientist who is ready to take their career to the next level while applying advanced analytics and machine learning to solve meaningful government challenges. This is more than a traditional role – it’s an opportunity to join a team that values your expertise, supports your growth, and allows you to focus on delivering impactful data solutions. Why Join Us? We are a mission-driven, team-first organization that puts your career and voice at the center of everything we do. When you join, you’ll step into a culture built on mentorship, professional growth, and innovation. You’ll have opportunities to advance into technical leadership, work with state-of-the-art tools, and collaborate in a flexible hybrid environment that supports your work-life balance. Responsibilities: Lead and perform advanced data analysis, modeling, and experimentation to develop actionable insights. Collaborate with mission stakeholders to define challenges, design approaches, and deliver robust project plans. Extract, clean, and transform large structured and unstructured datasets to build predictive models. Apply statistical and machine learning techniques to train, evaluate, and deploy models that support mission decisions. Identify patterns, anomalies, and trends in large datasets using advanced analytics. Communicate project designs, results, and recommendations clearly to both technical and non-technical audiences, including senior stakeholders. Must Have’s: Public Trust clearance Bachelor’s Degree (required) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience. 7-12 years of relevant experience Experience in applying advanced analytics solutions to solve complex business problems Experience with programming languages including: R, Python, JavaScript, Visual Basic Experience with creating VBA applications and macros to structure, manage, and wrangle key datasets Experience with core data science libraries – Pandas, NumPy, Matplotlib, Plotly, etc. Experience with Anaconda distribution of Python for package management and deployment Familiarity with command-line shell programming (Powershell, cmd, etc.) Proficiency with SQL programming Familiarity with RESTful APIs, web scraping, and processing unstructured data Knowledge of visualization and presentation techniques including Tableau, Power BI, Jupyter Notebooks, etc. Knowledge of cloud technologies such as AWS or Google Proficiency using git for version control, collaboration, and code review Familiarity with software organization tools and frameworks (Docker, virtual environments, etc.) Experience with engineering and development collaboration tools such as Jira and Confluence Experience with Natural Language Processing (NLP), computational linguistics, entity extraction, named entity recognition (NER), name matching, disambiguation Experience constructing and executing queries to extract data in support of EDA and model development Experience with unsupervised and supervised machine learning techniques and methods Experience working with large-scale (e.g., terabyte and petabyte) unstructured and structured datasets and databases Experience performing data mining, analysis, and training set construction Nice to Have’s: Proficiency with Unsupervised Machine Learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc. Proficiency with Supervised Machine Learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc. Experience with pattern recognition and extraction, automated classification, and categorization Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/disambiguation) Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI) Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop) Master’s Degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience Active Top Secret clearance Compensation & Benefits: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Parental Leave Basic Life Insurance Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Technology You’ll Use: Python, R, SQL, JavaScript Pandas, NumPy, Matplotlib, Plotly Tableau, Power BI, Jupyter Notebooks AWS & Google Cloud Platforms NLP and Machine Learning Frameworks (scikit-learn, TensorFlow, etc.) Big Data Tools (Hadoop, Spark, Kafka) Location HYBRID – Ashburn, VA, United States Salary $180-$215K
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HYBRID – Ashburn, VA, United States Data Scientist We are seeking a Data Scientist who is ready to take their career to the next level while applying advanced analytics and machine learning to solve meaningful government challenges. This is more than a traditional role – it’s an opportunity to join a team that values your expertise, supports your growth, and allows you to focus on delivering impactful data solutions. Why Join Us? We are a mission-driven, team-first organization that puts your career and voice at the center of everything we do. When you join, you’ll step into a culture built on mentorship, professional growth, and innovation. You’ll have opportunities to advance into technical leadership, work with state-of-the-art tools, and collaborate in a flexible hybrid environment that supports your work-life balance. Responsibilities: Lead and perform advanced data analysis, modeling, and experimentation to develop actionable insights. Collaborate with mission stakeholders to define challenges, design approaches, and deliver robust project plans. Extract, clean, and transform large structured and unstructured datasets to build predictive models. Apply statistical and machine learning techniques to train, evaluate, and deploy models that support mission decisions. Identify patterns, anomalies, and trends in large datasets using advanced analytics. Communicate project designs, results, and recommendations clearly to both technical and non-technical audiences, including senior stakeholders. Must Have’s: Public Trust clearance Bachelor’s Degree (required) in operations research, industrial engineering, mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience. 7-12 years of relevant experience Experience in applying advanced analytics solutions to solve complex business problems Experience with programming languages including: R, Python, JavaScript, Visual Basic Experience with creating VBA applications and macros to structure, manage, and wrangle key datasets Experience with core data science libraries – Pandas, NumPy, Matplotlib, Plotly, etc. Experience with Anaconda distribution of Python for package management and deployment Familiarity with command-line shell programming (Powershell, cmd, etc.) Proficiency with SQL programming Familiarity with RESTful APIs, web scraping, and processing unstructured data Knowledge of visualization and presentation techniques including Tableau, Power BI, Jupyter Notebooks, etc. Knowledge of cloud technologies such as AWS or Google Proficiency using git for version control, collaboration, and code review Familiarity with software organization tools and frameworks (Docker, virtual environments, etc.) Experience with engineering and development collaboration tools such as Jira and Confluence Experience with Natural Language Processing (NLP), computational linguistics, entity extraction, named entity recognition (NER), name matching, disambiguation Experience constructing and executing queries to extract data in support of EDA and model development Experience with unsupervised and supervised machine learning techniques and methods Experience working with large-scale (e.g., terabyte and petabyte) unstructured and structured datasets and databases Experience performing data mining, analysis, and training set construction Nice to Have’s: Proficiency with Unsupervised Machine Learning methods including Cluster Analysis (e.g., K-means, K-nearest Neighbor, Hierarchical, Deep Belief Networks, Principal Component Analysis), Segmentation, etc. Proficiency with Supervised Machine Learning methods including Decision Trees, Support Vector Machines, Logistic Regression, Random/Rotation Forests, Categorization/Classification, Neural Nets, Bayesian Networks, etc. Experience with pattern recognition and extraction, automated classification, and categorization Experience with entity resolution (e.g., record linking, named-entity matching, deduplication/disambiguation) Experience with visualization tools and techniques (e.g., Periscope, Business Objects, D3, ggplot, Tableau, SAS Visual Analytics, PowerBI) Experience with big data technologies (e.g., Hadoop, HIVE, HDFS, HBase, MapReduce, Spark, Kafka, Sqoop) Master’s Degree in mathematics, statistics, computer science/engineering, or other related technical fields with equivalent practical experience Active Top Secret clearance Compensation & Benefits: Medical, Rx, Dental & Vision Insurance Personal and Family Sick Time & Company Paid Holidays Parental Leave Basic Life Insurance Tuition Reimbursement, Personal Development & Learning Opportunities Skills Development & Certifications Employee Referral Program Technology You’ll Use: Python, R, SQL, JavaScript Pandas, NumPy, Matplotlib, Plotly Tableau, Power BI, Jupyter Notebooks AWS & Google Cloud Platforms NLP and Machine Learning Frameworks (scikit-learn, TensorFlow, etc.) Big Data Tools (Hadoop, Spark, Kafka) Location HYBRID – Ashburn, VA, United States Salary $180-$215K
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