Lead Data Scientist – Solution Architect

This is a fully remote position, open to applicants in United States.

📋 Description

• Act as the architectural lead for intricate data science, AI, machine learning, forecasting, optimization, and advanced analytics projects.

• Collaborate with clients to comprehend business challenges, gather requirements, identify data constraints, and transform business needs into scalable technical solutions.

• Design and oversee production-ready solutions utilizing Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Synapse Analytics, Databricks, Spark, Power BI, and other relevant Microsoft technologies.

• Provide technical guidance on model design, algorithm selection, data preparation, feature engineering, training, validation, deployment, monitoring, and optimization.

• Lead architectural decisions concerning compute configuration, GPU acceleration, model performance, scalability, deployment patterns, and Azure cost/performance optimization.

• Serve as a subject matter expert for internal teams and clients regarding data science architecture, AI strategy, machine learning engineering, and advanced analytics delivery.

• Facilitate client-facing discovery and requirements-gathering sessions.

• Assist project teams in navigating ambiguous, incomplete, or challenging data environments.

• Convey complex analytical and technical concepts to both technical and business stakeholders.

• Provide actionable recommendations based on model outputs, business implications, risks, limitations, and opportunities for improvement.

• Support Statements of Work, proposals, solution estimates, technical approach documentation, and project plans.

• Collaborate with data engineers, data architects, project managers, business analysts, and client stakeholders.

• Directly manage, mentor, and assist a Senior Data Scientist Consultant.

• Offer coaching, feedback, and technical guidance; review technical deliverables, model designs, code quality, documentation, and client-facing outputs.

• Support performance management, goal setting, skills development, and career advancement for direct reports.

• Develop, review, and oversee predictive, statistical, optimization, forecasting, and analytical models.

• Employ advanced statistical and machine learning techniques on large structured and unstructured datasets.

• Utilize Python for model development, data exploration, experimentation, and production-ready analytical solutions.

• Create and assess deep learning models using PyTorch.

• Assist in the deployment, monitoring, drift detection, availability, and performance measurement of production models.

• Lead experimentation and model validation to guarantee accurate, explainable solutions aligned with business outcomes.

⛳️ Requirements

• 10+ years of practical experience in data science, machine learning, AI, advanced analytics, or related technical fields.

• Previous experience in technical architecture, lead data scientist, principal data scientist, AI/ML architect, or a similar senior-level position.

• Strong proficiency in Python for data science, machine learning, deep learning, statistical modeling, and production-level solutions.

• Familiarity with Spark and large-scale data processing.

• Extensive experience with Azure-based data and AI technologies, including Azure Machine Learning and related Azure data services.

• Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, M365 Agents, or comparable AI/agent frameworks.

• Practical experience with PyTorch for deep learning model development.

• Strong grounding in statistics, regression, forecasting, optimization, and machine learning methodologies.

• Experience in developing, deploying, owning, and monitoring production-level machine learning models.

• Ability to assess and implement time-series and forecasting techniques such as ARIMA, TBATS, Temporal Fusion Transformer, Prophet, or similar methodologies.

• Experience working with structured, semi-structured, and unstructured data.

• Familiarity with connecting to and utilizing data platforms such as data lakes, data warehouses, APIs, NoSQL databases, and cloud-native data services.

• Ability to convert business needs into technical requirements through active collaboration with clients, stakeholders, data scientists, data engineers, and data architects.

• Strong communication and storytelling skills, with the capability to elucidate technical concepts and model outputs to non-technical audiences.

• Proven ability to lead complex client-facing engagements and manage multiple priorities.

• Strong problem-solving mindset characterized by curiosity, perseverance, and the ability to navigate incomplete systems or ambiguous data challenges.

• Experience mentoring, coaching, or managing technical team members.

• Must be willing to travel approximately 10% as needed.

• Master’s or Ph.D. preferred in Computer Science, Statistics, Applied Mathematics, Data Science, Engineering, Operations Research, or a related discipline.

• Solid academic foundation in statistics, computer science, mathematics, optimization, or research-based analytical methods.

• Published research, thesis work, National Academy of Sciences affiliation, or other indications of research depth.

• Experience in manufacturing, supply chain, demand forecasting, inventory optimization, quality analytics, production analytics, or industrial operations.

• Experience with cloud-native or ML-native organizations, research-intensive environments, or teams focused on algorithmic optimization.

• Familiarity with C++, GPU acceleration, distributed training, or compute optimization.

• Experience configuring Azure compute environments for machine learning performance, scalability, and cost efficiency.

• Experience with Databricks, Azure Databricks, or equivalent big data and ML engineering platforms.

• Experience in supporting proposal development, solution estimation, technical sales support, or pre-sales activities.

• Prior consulting experience in a client-facing technical leadership role.

🏝️ Benefits

• Quarterly supplemental bonus compensation.

• Unlimited Paid Time Off (UPTO).

• 401k Plan with Company Matching Contribution.

• Monthly Stipend for Home Office Expenses.

• Subsidized Medical, Dental and Vision Coverage.

• Health Savings and Flexible Spending Accounts.

• Company Paid Life and Disability Insurance.

• Training, Certification and Continuing Education Support.

• Personal and professional growth opportunities.