Senior Data Scientist

Remote, United States

Description

ActioNet has an exciting opportunity for a Senior Data Scientist to join our team to lead digital transformation projects to develop and implement future mission-critical enterprise data analytics and production systems for the nation’s premiere source of statistical data products.

The Senior Data Scientist will provide full lifecycle data management including the design of highly scalable cloud-native architectures to support automated dynamic data collection, integration, storage, transformation, harmonization, analysis, reporting and dissemination needs. This includes providing advanced subject matter expertise in AI/ML, data modeling, statistics, and data privacy protection. This role demands expertise in Python and involves building complex pipelines from scratch, managing data flow within the AWS ecosystem, and conducting rigorous testing to ensure accuracy and completeness, consistency, and quality of all outputs. This position requires a leader, innovator and problem-solver with solid data science, statistical, and programming experience. This position also requires experience developing and designing new projects and solutions, coordinating projects between multiple teams with many stakeholders in a pro-active, enthusiastic communication style.

This position is REMOTE.  

Federal position requires Public Trust.  Candidates must be US Citizens to be eligible. 

Responsibilities: 

• Serve as the technical authority for enterprise and solution-level data architecture, guiding the design and modernization of complex application ecosystems.
• Collaborate with data scientists, analysts, and other stakeholders to understand data requirements and deliver tailored data solutions.
• Assess legacy and on-premises data environments and define cloud migration and modernization strategies including rehost, re-platform, refactor, and cloud-native redesign
• Define target-state data architectures that support front-end applications, API platforms, enterprise databases, queueing systems, scalable computation engines, and analytical services.
• Develop efficient data processing and transformation workflows to support analytics and reporting needs. Define architectures for computation engines that execute Python-based analytical workloads and large-scale data processing.
• Architect data platforms integrating RDBMS and cloud-native object storage for large-scale transactional and analytical workloads and secure AWS-based data infrastructure leveraging EMR, Apache Spark, and PySpark.
• Lead the architectural design of microservices-based data platforms emphasizing API-first integration, loose coupling, stateless and stateful service separation, and elastic scalability.
• Lead testing, evaluation, and presentation of technological and/or methodological alternatives and recommend improvements.
• Implement processes for data cleaning, transformation, and validation to ensure data accuracy, consistency, and compliance with security and privacy policies.
• Design, build, and maintain data pipelines and automated extract, transform, load (ETL)  processes using tools like Python, R, and platform‑specific environments such as Jupyter Notebooks.
• Integrate disparate structured and unstructured data from APIs, databases, and cloud storage into unified datasets utilizing ETL patterns, frameworks, query techniques.

• Develop dashboards, visualizations, and analytical products to support operational decision‑making.
• Develop metrics to evaluate statistical accuracy and code performance.
• Optimize code through advanced algorithmic concepts to facilitate more efficiency.
• Provide full lifecycle assistance in deploying, optimizing, maintaining complex code with data processing routines running in development, test, and production.

Requirements:

• 5+ years of experience as a Data Scientist, Data Engineer, Backend Software Engineer, or similar.
• Bachelor’s degree from an accredited college or university with a major in computer science, statistics, mathematics, economics, or related field.
• Strong skills in Python, R, and SQL.
• Proficient in handling large-scale data projects involving data integration, cleaning, ETL, analysis, aggregation, tabulation, and reporting.
• Experience with data privacy protection and related statistical methodologies is a plus.
• Experience developing and implementing data reliability, efficiency, and quality checks and processes.
• Experience leveraging AWS services (e.g., S3, EMR, Glue, Lambda, Athena, Redshift, SageMaker, QuickSight) to build and deploy data solutions in a cloud-native environment.
• Experience with structured and unstructured databases (such as Oracle, PostGreSQL, MySQL, Athena, Redshift, MongoDB etc).
• Experience working in an Agile organization using Scrum, Kanban, Jira, Confluence, and SAFe.
• Experience with GitHub, Subversion, or other source control systems.
• Experience managing, testing, and deploying software components within SDLC.
• Knowledge of DevOps practices and tools (e.g., Jenkins, GitLab CI/CD).
• Excellent communication and teamwork skills.
• Demonstrated understanding of project management, schedules, and how to estimate the level of effort for development tasks.
• Experience evaluating proposed systems and recommending improvements; Strong skills preparing and presenting design/architectural documents to clients.
• Requires a Public Trust - must be US Citizen to be eligible. 

Preferred Qualifications:

• Experience with and interest in AI/ML, statistics, data modeling, and advanced math highly preferred.
• Experience with SAS, Apache Spark, PySpark preferred.
• Experience with Optimization Theory or Gurobi model development preferred, but not required.
• Experience with data platforms such as Cube, Athena, Redshift, Databricks, Palantir, Snowflake, Google BigQuery.

• Familiarity with distributed high-performance computing (HPC) and parallel processing.

• Familiarity with demographic, economic, longitudinal, and geospatial data sources and structures.
• Experience with microservices architecture and containerization (e.g., Docker, Ansible, Kubernetes).

• Advanced and Managed IT Services
• Agile Software Development
• DevSecOps
• Cybersecurity
• Health IT
• C4ISR & SIGINT
• Data Center Engineering & Operations
• Engineering & Installation

• Commitment to Employees: We are committed to making ActioNet a great place to work and continue to invest in our ActioNeters.
• Commitment to Customers: We are committed to our customers by driving and sustaining Service Delivery Excellence.
• Commitment to Community: We are committed to giving back to our community, helping others, and making the world a better place for our next generation. 

• Medical Insurance
• Vision Insurance
• Dental Insurance
• Life and AD&D Insurance
• 401(k) Savings Plan
• Education and Professional Training
• Flexible Spending Accounts (FSA)
• Employee Referral and Merit Recognition Programs
• Employee Assistance and Identity Theft Protection
• Paid Holidays: 11 per year
• Paid Time Off (PTO)
• Disability Insurance