Data-driven consulting and technology services
Senior Data Scientist
Location
Virginia
Posted
2 days ago
Salary
0
Seniority
Senior
Job Description
Senior Data Scientist
Analytica
• Develop and deploy advanced analytics, machine learning, NLP, and AI solutions supporting mission and client objectives. • Develop and enhance generative AI and RAG solutions using large language models, embeddings, vector databases, retrieval strategies, prompt engineering techniques, and cloud-based AI services. • Leverage modern data and AI platforms to accelerate solution delivery and operationalize machine learning capabilities. • Perform data acquisition, ETL, exploratory data analysis, data preparation, and validation activities using Python, SQL, and related technologies to support analytics and AI initiatives. • Apply statistical methods, predictive modeling, machine learning, and time-series analysis to solve complex business and operational challenges. • Develop, test, evaluate, and monitor AI/ML solutions to ensure accuracy, reliability, scalability, security, and performance in production environments. • Partner with stakeholders and clients to gather requirements, translate business needs into technical solutions, and communicate findings and recommendations to technical and non-technical audiences. • Develop and troubleshoot APIs, data services, and AI-enabled applications while supporting integration with enterprise systems and cloud platforms. • Contribute to collaborative software development using Git-based version control, code reviews, Agile methodologies, and established development best practices. • Produce technical documentation, presentation materials, implementation guidance, and knowledge-transfer artifacts to support project delivery and long-term sustainment. • Serve as an innovative technical contributor by evaluating emerging technologies, identifying opportunities to improve existing processes and solutions, and applying modern data science and AI capabilities to solve complex business problems. • Collaborate effectively across multidisciplinary teams and contribute to a culture of continuous improvement and knowledge sharing.
Job Requirements
- Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related technical field; Master's degree preferred.
- Five or more years of experience developing data science, analytics, machine learning, or AI solutions, including experience leading technical tasks and contributing to complex projects.
- Strong proficiency in Python and SQL for data preparation, analytics, model development, testing, and deployment.
- Experience designing, developing, validating, and monitoring machine learning models, including feature engineering, model evaluation, and performance optimization.
- Working knowledge of modern AI and natural language processing concepts, including large language models, embeddings, vector databases, prompt engineering, retrieval approaches, and output evaluation.
- Experience developing API-based solutions and integrating data, machine learning, and AI services into enterprise environments.
- Experience with Databricks is preferred.
- Familiarity with AWS cloud services and AI platforms such as Amazon Bedrock is a plus.
- Familiarity with object-oriented structures and design (classes, inheritance, abstraction, etc).
- Experience collaborating in a team development environment using Git, code reviews, Agile workflows, and software development best practices.
- Strong communication and problem-solving skills with the ability to present technical concepts and recommendations to both technical and non-technical audiences.
- Demonstrated ability to work independently as a self-starter, learn new technologies quickly, manage competing priorities, and communicate effectively across technical and non-technical teams.
Benefits
- Competitive compensation
- Bonus opportunities
- Employer-paid healthcare
- Professional development funding
- 401(k) match
Related Guides
Related Categories
Related Job Pages
More Data Scientist Jobs
• Lead analytics initiatives from problem definition through to insight delivery and business adoption • Partner with Marketing, BI, IS, and other teams to understand challenges • Translate complex analysis into clear, actionable insights • Deliver analysis that informs segmentation, retention, campaign performance, and customer strategy • Design experiments, iterate quickly, and continuously improve impact • Work hands-on across the data lifecycle and apply advanced analytics and ML techniques to problems • Collaborate effectively across a geographically dispersed team
• Define, own, and execute a multi-year roadmap for data protection and cryptographic services, maturing the program from operational to industry-leading. • Establish and enforce data protection policies, standards, and frameworks aligned with industry best practices (NIST, ISO 27001, SOC 2, GDPR, CCPA, and emerging AI governance standards). • Serve as the company's authoritative source on data protection strategy, advising executive leadership on risk posture and investment priorities. • Lead the architecture, deployment, and continuous improvement of the full DLP ecosystem, including Web Proxies & SSL Inspection, Cloud Access Security Broker (CASB), Data Classification & Tagging, Data Security Posture Management (DSPM), and AI Security Posture Management (AI-SPM). • Own vendor relationships, contract negotiations, and technology roadmap alignment for all data protection tooling. • Oversee the company's cryptographic standards and practices, including key management, PKI, encryption-at-rest and in-transit standards, and secrets management. • Drive adoption of modern cryptographic controls across engineering teams, ensuring alignment with evolving standards and quantum-readiness planning. • Set expectations, manage performance, and build a high-trust team environment where engineers do their best work.
• Lead multiple product initiatives end-to-end—from discovery and validation through delivery and adoption. • Drive adoption and maturity of data mesh and data platform capabilities across engineering, analytics, and product teams. • Build scalable, simplified data systems that reduce complexity and unlock durable customer value. • Partners with engineering, design, program management, and vertical market teams to define and execute product strategy. • Prioritize and sequence backlogs with rigor, transparency, and business-outcome alignment. • Identify and solve cross-team problems proactively, removing ambiguity and driving clarity for global partners.
• You will be one of the early data science hires shaping how Purpose understands the clients on our wealth platform. • You'll build the measurement architecture, behavioral models, and causal infrastructure that connects product decisions to client outcomes. • Determine what is worth measuring in a platform generating thousands of behavioral signals. • Design AI analytics systems with the rigor of a statistician.



