Lead Data Scientist – Solution Architect

Role Overview

The Azure Data Science Architect is responsible for providing technical leadership, architectural direction, and hands-on guidance across complex data science, AI, machine learning, and advanced analytics initiatives for MCA Connect clients.

What You Will Do

The ideal candidate will bring deep expertise in machine learning and AI development, Azure data and AI services, statistical modeling, forecasting, optimization, and production model deployment.

Why It Might Be a Fit

The ideal candidate is a hands-on technical architect who can operate at both the strategic and execution level, with strong academic or practical depth in data science and machine learning.

Requirements

• 10+ years of hands-on experience in data science, machine learning, AI, advanced analytics, or related technical disciplines.
• Prior experience in technical architecture, lead data scientist, principal data scientist, AI/ML architect, or similar senior-level role.
• Strong proficiency in Python for data science, machine learning, deep learning, statistical modeling, and production-level solutions.
• Experience with Spark and large-scale data processing.
• Strong experience with Azure-based data and AI technologies, including Azure Machine Learning and related Azure data services.
• Hands-on experience with PyTorch for deep learning model development.
• Strong foundation in statistics, regression, forecasting, optimization, and machine learning methodology.
• Experience developing, deploying, owning, and monitoring production-level machine learning models.
• Ability to evaluate and apply time-series and forecasting techniques such as ARIMA, TBATS, Temporal Fusion Transformer, Prophet, or similar methods.
• Experience working with structured, semi-structured, and unstructured data.
• Experience connecting to and working with data platforms such as data lakes, data warehouses, APIs, NoSQL databases, and cloud-native data services.
• Ability to translate business needs into technical requirements through active partnership with clients, stakeholders, data scientists, data engineers, and data architects.
• Strong communication and storytelling skills, with the ability to explain technical concepts and model outputs to non-technical audiences.
• Demonstrated ability to lead complex client-facing engagements and manage multiple priorities.
• Strong problem-solving mindset with curiosity, perseverance, and the ability to work through incomplete systems or ambiguous data challenges.
• Experience mentoring, coaching, or managing technical team members.

Benefits

• Work/Life Balance with 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

Tagged as: Forecasting, Python