Solution Architect, Data Science

About Our Client

This organization operates in the data and AI consulting industry, supporting enterprises across sectors like Energy & Utilities, Media & Entertainment, Manufacturing, and Retail & CPG. They address challenges related to modernizing data infrastructure and deploying AI solutions in production environments. Their services cover the full data and AI lifecycle including strategy, engineering, analytics, generative AI, and cloud migration, primarily on the Databricks platform with partnerships across AWS, Azure, and GCP. The organization has contributed over $2 billion in business value to Fortune 500 clients and has rapidly grown from 85 to over 500 employees while maintaining a technically focused and collaborative culture.

About the Opportunity

The Solution Architect, Data Science is responsible for leading technical strategy and design of enterprise-grade machine learning and advanced analytics solutions, particularly on the Databricks platform. This role influences client engagements from initial scoping through delivery, shaping business-value metrics and guiding cross-functional teams to build scalable AI/ML applications. The position requires bridging technical execution with executive communication to ensure high-impact outcomes and client success.

Responsibilities

• Define business-value metrics and technical performance targets for engagements
• Lead technical scoping, feasibility assessments, and solution design for proposals and client pitches
• Design scalable, secure, and maintainable end-to-end ML pipelines including data analysis, feature engineering, model training, deployment, and MLOps
• Direct delivery teams of Data Scientists, Data Engineers, and ML Engineers to align with architectural standards
• Establish code quality standards, model validation protocols, and best practices to ensure reliability
• Communicate technical concepts and risks clearly to both technical teams and C-suite stakeholders
• Design operational workflows and user integration strategies to drive AI/ML tool adoption
• Conduct client enablement workshops and knowledge transfer for solution sustainability
• Build rapid prototypes, presales presentations, and proofs of concept for client engagements

Requirements

• B.S. or M.S. in Computer Science, Engineering, Economics, or related quantitative field
• 7+ years of experience in Data Science & AI/ML including large-scale deployments
• 4+ years in client-facing roles, preferably in professional services
• Experience designing and implementing data science solutions in at least two areas such as forecasting, anomaly detection, recommendation systems, computer vision, propensity modeling, or optimization
• Expert knowledge of Python and SQL and hands-on experience with Databricks tools (Unity Catalog, MLFlow, Delta Tables)
• Proficiency with commercial and open-source LLM APIs and tools like Hugging Face Transformers and LangChain
• Experience with rapid prototyping, presales presentations, and pricing engagements
• Strong client communication skills capable of influencing technical and executive stakeholders
• Prior experience with fraud detection, risk modeling, or anomaly prevention systems

Pay Range and Compensation Package

The base salary range for candidates based in the US is $155,000 to $190,000 per year. Compensation is based on experience, skills, qualifications, role scope, and budget. Most offers fall within the middle or below the stated range. The organization is committed to pay equity and transparency.