数据科学家负责人 - 解决方案架构师
Lead Data Scientist - Solution Architect
通过热情和深厚的行业专业知识,MCA Connect 通过可操作的业务洞察力帮助制造商取得成功。我们的战略解决方案、创新和行业洞察力帮助制造商获得可见性,提高盈利能力,并获得竞争优势。
自2002年成立以来,MCA Connect 已成长为美国最大的微软业务应用和 Azure 数据与 AI / 数字与应用创新解决方案合作伙伴之一。我们的微软专业领域包括财务与供应链、Azure 上的分析、数据仓库迁移以及 Power Platform。我们曾15次获得微软合作伙伴年度奖,并3次获得 Inc. 最佳工作场所奖。
首席数据科学家 - 解决方案架构师
地点
远程办公,根据需要偶尔前往客户现场
用工类型
全职
职位概述
Azure 数据科学架构师负责为 MCA Connect 客户在复杂的数据科学、AI、机器学习和高级分析项目中提供技术领导力、架构方向和实际指导。该角色将作为高级技术顾问和解决方案负责人,帮助客户将业务问题转化为可扩展的、生产就绪的 AI 和数据科学解决方案。
除了个人技术领导力,该角色还将包含人员管理部分。Azure 数据科学架构师将直接管理并指导一位高级数据科学家,对技术质量、交付执行、客户沟通、职业发展以及与 MCA 标准和最佳实践的一致性进行监督。
理想的候选人应具备机器学习和 AI 开发的深厚专业知识,熟悉 Azure 数据与 AI 服务、统计建模、预测、优化和生产模型部署。该人应能够直接与客户互动,处理混乱或不完整的数据环境,提供架构建议,并带领技术和非技术利益相关者解决复杂的分析解决方案。
主要职责
解决方案架构与技术领导
- 作为复杂的数据科学、AI、机器学习、预测、优化和高级分析项目的架构负责人。
- 与客户合作,了解业务挑战,收集需求,识别数据限制,并将业务需求转化为可扩展的技术解决方案。
- 设计并指导技术方案的实施,确保符合行业最佳实践和客户需求。
查看英文原文
Through passion and deep industry expertise, MCA Connect helps manufacturers succeed by unlocking innovation with actionable business insights. Our strategic solutions, innovation, and industry intelligence help manufacturers gain visibility, improve profitability, and achieve a competitive edge.
Established in 2002, MCA Connect has grown into one of the largest US-based solution partners in Microsoft Business Applications and Azure Data & AI / Digital & App Innovation. Our Microsoft Specialties include Finance and Supply Chain, Analytics on Azure, Data Warehouse Migration, and Power Platform. We’re also a fifteen-time Microsoft Partner of the Year and three-time Inc. Best Workplaces award winner.
Lead Data Scientist - Solution Architect
Location
Remote with light travel as needed to client sites
Employment Type
Full-time
Position Summary
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. This role will serve as a senior technical advisor and solution owner, helping clients translate business problems into scalable, production-ready AI and data science solutions.
In addition to individual technical leadership, this role will include a people management component. The Azure Data Science Architect will directly manage and mentor a Senior Data Scientist, providing oversight on technical quality, delivery execution, client communication, professional development, and alignment to MCA’s standards and best practices.
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. This person should be comfortable engaging directly with customers, working through messy or incomplete data environments, providing architectural recommendations, and leading both technical and non-technical stakeholders through complex analytical solutions.
Key Responsibilities
Solution Architecture & Technical Leadership
- Serve as the 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 the implementation of production-ready data science and AI 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.
- Evaluate and recommend appropriate modeling approaches, including regression techniques, forecasting models, deep learning methods, optimization algorithms, and advanced statistical approaches.
- Lead architecture decisions related to compute configuration, GPU acceleration, model performance, scalability, deployment patterns, and Azure cost/performance optimization.
- Ensure solutions are designed for long-term maintainability, scalability, observability, and business value.
- Stay current with emerging Microsoft data, AI, and agent technologies, including Azure AI Foundry, M365 Agents, Azure OpenAI, and related tools.
- Act as a subject matter expert for internal teams and clients on data science architecture, AI strategy, machine learning engineering, and advanced analytics delivery.
Delivery & Client Engagement
- Lead client-facing discovery and requirement gathering sessions to define project goals, business outcomes, technical requirements, and success measures.
- Work directly with customers to understand business processes, analytical needs, data maturity, and operational constraints.
- Guide project teams through ambiguous, incomplete, or messy data environments by diagnosing issues, proposing solutions, and escalating appropriately when needed.
- Communicate complex analytical and technical concepts clearly to both technical teams and business stakeholders.
- Deliver actionable recommendations that help clients understand model outputs, business implications, risks, limitations, and opportunities for improvement.
- Support the development of Statements of Work, proposals, solution estimates, technical approach documentation, and project plans as needed.
- Collaborate with data engineers, data architects, project managers, business analysts, and client stakeholders to ensure successful end-to-end delivery.
- Ensure data science solutions align to client goals, MCA delivery standards, Microsoft best practices, and long-term supportability.
People Management & Mentorship
- Directly manage, mentor, and support a Senior Data Scientist Consultant.
- Provide regular coaching, feedback, and technical guidance to support professional growth and project success.
- Review technical deliverables, model design decisions, code quality, documentation, and client-facing outputs.
- Help prioritize work, remove blockers, and ensure the Senior Data Scientist Consultant is aligned to project goals and client expectations.
- Support performance management, goal setting, skills development, and career growth for direct report(s).
- Foster a collaborative, curious, and high-accountability team culture.
- Partner with Data & AI leadership to identify opportunities for team improvement, knowledge sharing, reusable assets, and delivery process enhancements.
Data Science, AI & Machine Learning Expertise
- Build, review, and guide the development of predictive models, statistical models, optimization models, forecasting solutions, and other analytical applications.
- Apply advanced statistical and machine learning methods to large, complex structured and unstructured datasets.
- Use Python as the primary programming language for model development, data exploration, experimentation, and production-ready analytical solutions.
- Work with Spark and large-scale data processing frameworks to support high-volume analytics and machine learning workloads.
- Develop and evaluate deep learning models using PyTorch.
- Apply and explain multiple regression techniques, time-series approaches, and forecasting models.
- Work with algorithms and methods such as ARIMA, TBATS, Temporal Fusion Transformer, Prophet, and other relevant forecasting or optimization techniques.
- Support production model deployment, monitoring, drift detection, availability, and performance measurement.
- Lead experimentation and model validation processes to ensure solutions are accurate, explainable, and aligned with business outcomes.
- Avoid over-reliance on AutoML by demonstrating hands-on coding ability, critical thinking, and strong foundational understanding of machine learning and statistical methods.
Required Qualifications
- 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.
Preferred Qualifications
- Master’s or Ph.D. 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.
Ideal Candidate Profile
The ideal candidate is a hands-on technical architect who can operate at both the strategic and execution level. This person should be able to sit with a client to understand a business problem, evaluate the available data, define the technical path forward, guide the modeling and architecture approach, and mentor a Senior Data Scientist Consultant through successful delivery.
They should bring strong academic or practical depth in data science and machine learning, but also the communication skills and consulting mindset needed to work directly with manufacturing and supply chain clients. They should be comfortable with ambiguity, curious enough to investigate messy data environments, and experienced enough to know when to escalate, simplify, optimize, or re-architect a solution.
This role is best suited for someone who is not solely reliant on AutoML or out-of-the-box tools, but instead has the hands-on coding ability, statistical foundation, and architectural judgment to build scalable, client-ready AI and machine learning solutions.
Why work for MCA Connect?
Our compensation plan offers one of the best bonus structures in the industry. Along with this we also offer a generous benefit package:
·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
MCA Connect offers limitless opportunities for personal and professional growth in a stimulating, challenging, and performance-oriented work culture where you can share your ideas and make impactful daily contributions. Our employees are highly motivated and talented individuals dedicated to developing, marketing, and selling products designed to deliver value for mid-market and enterprise-size manufacturing, distribution, and energy companies. We take the time to train our consultants so that they understand the industries we serve and can deliver best practices, proven methodologies, and ongoing industry expertise to our clients.
MCA Connect is an Equal Opportunity Employer. MCA Connect promotes equal employment opportunity to all employees and applicants and does not discriminate on the basis of race, religion, color, creed, national origin, sex, age, sexual/gender orientation, status as a protected disabled or Vietnam Era Veteran, disability, or any other legally protected status. We firmly believe our differences make us stronger!
Originally posted on Himalayas