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Lead Data Scientist – Solution Architect
MCA Connect. Serve as architectural lead for complex data science, AI, machine learning, forecasting, optimization, and advanced analytics engagements .
Tech Stack
Tools & technologiesAzureCloudNoSQLPythonPyTorchSparkC++
About the role
Key responsibilities & impact- Serve as architectural lead for complex data science, AI, machine learning, forecasting, optimization, and advanced analytics engagements
- Partner with clients to understand business challenges, gather requirements, identify data limitations, and translate business needs into scalable technical solutions
- Design and guide production-ready solutions using Azure Machine Learning, Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Synapse Analytics, Databricks, Spark, Power BI, and related Microsoft technologies
- Provide technical direction on model design, algorithm selection, data preparation, feature engineering, training, validation, deployment, monitoring, and optimization
- Lead architecture decisions related to compute configuration, GPU acceleration, model performance, scalability, deployment patterns, and Azure cost/performance optimization
- Act as a subject matter expert for internal teams and clients on data science architecture, AI strategy, machine learning engineering, and advanced analytics delivery
- Lead client-facing discovery and requirements-gathering sessions
- Guide project teams through ambiguous, incomplete, or messy data environments
- Communicate complex analytical and technical concepts to technical and business stakeholders
- Deliver actionable recommendations about model outputs, business implications, risks, limitations, and improvement opportunities
- 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 support a Senior Data Scientist Consultant
- Provide 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 growth for direct reports
- Build, review, and guide predictive, statistical, optimization, forecasting, and analytical models
- Apply advanced statistical and machine learning methods to large structured and unstructured datasets
- Use Python for model development, data exploration, experimentation, and production-ready analytical solutions
- Develop and evaluate deep learning models using PyTorch
- Support production model deployment, monitoring, drift detection, availability, and performance measurement
- Lead experimentation and model validation to ensure accurate, explainable solutions aligned with business outcomes
Requirements
What you’ll need- 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
- Experience with Azure AI Foundry, Azure OpenAI, Azure AI Search, M365 Agents, or similar AI/agent frameworks
- 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
- Must be open to approximately 10% travel as needed
- Master's or Ph.D. preferred in Computer Science, Statistics, Applied Mathematics, Data Science, Engineering, Operations Research, or a related field
- Strong academic foundation in statistics, computer science, mathematics, optimization, or research-based analytical methods
- Published research, thesis work, National Academy of Sciences affiliation, or other demonstrated 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-heavy environments, or algorithmic optimization-focused teams
- Experience 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 supporting proposal development, solution estimation, technical sales support, or pre-sales activities
- Prior consulting experience in a client-facing technical leadership role
Benefits
Comp & perks- 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