Architect, Data Science

Lovelytics • Arlington, VA

2d • $140,000 - $210,000

About The Position

Lovelytics is seeking a Data Scientist Architect with hands-on experience delivering client-facing, enterprise-grade machine learning and advanced analytics solutions, particularly on Databricks. As part of the growing Data Science practice, the role leads technical strategy, designs end-to-end ML pipelines, and drives pre-sales engagements from initial scoping through final delivery. The Architect defines business-value metrics, shapes client proposals, and directs cross-functional delivery teams building scalable AI/ML applications. The position calls for deep technical expertise in predictive modeling and modern AI frameworks, together with consulting acumen to influence technical teams and C-suite executives.

The role supports projects across industries and the data and AI lifecycle, primarily using Databricks and working with cloud partners AWS, Azure, and GCP. It includes client-facing solution design and delivery, technical presales, client enablement, and knowledge transfer. This position is not eligible for work sponsorship at this time.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, Economics, or a related field.
• At least 7 years of experience in data science and AI/ML, including large-scale solution deployments.
• At least 5 years of experience in a client-facing role, preferably at a professional services firm.
• Strong communication skills and ability to influence technical and executive stakeholders.
• Demonstrated experience designing and implementing modern data science solutions in at least two of these areas: forecasting, anomaly detection, recommendation systems, computer vision, risk modeling, or mathematical optimization.
• Expert knowledge of Python and SQL, and strong hands-on Databricks experience, including Unity Catalog, MLflow, and Delta Tables.
• Proficiency with commercial and open-source LLM APIs and tools such as Hugging Face, LangChain, and DSPy, as well as coding assistants.
• Experience with rapid prototyping, proof-of-concept development, technical presales presentations, and engagement pricing.

Nice To Haves

• Prior experience with revenue management, price modeling, and causal inference.

Responsibilities

• Define business-value metrics, such as ROI, revenue impact, and cost reduction, alongside technical performance targets for engagements.
• Lead technical scoping, feasibility assessments, and solution design for proposals, Statements of Work, and client pitches.
• Design scalable, secure, maintainable end-to-end multi-layer ML/AI pipelines spanning data analysis, feature engineering, model training, deployment, and MLOps.
• Direct cross-functional teams of Data Scientists, Data Engineers, and ML Engineers to deliver solutions aligned with architectural standards.
• Establish code quality standards, model validation protocols, and technical best practices to prevent technical debt and ensure system reliability.
• Explain technical concepts, model trade-offs, and operational risks to technical teams and non-technical C-suite stakeholders.
• Design operational workflows and user integration strategies that encourage end-user adoption of AI/ML tools.
• Conduct client enablement workshops and knowledge-transfer sessions to build internal capability and support long-term solution sustainability.

Benefits

• Meaningful, cutting-edge Data Science and AI/ML projects with clients ranging from Fortune 500 firms to disruptive startups.
• Rapid learning and mentorship opportunities with Data & AI thought leaders and practitioners.
• A culture of experimentation, innovation, and continuous improvement.
• Opportunity to be a conference speaker, blogger, and writer.
• A diverse, inclusive, and collaborative team culture where employees’ voices and ideas are heard.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal