{"id":1276534,"url":"https://alion.io/job/mca-connect-lead-data-scientist-solution-architect","title":"Lead Data Scientist - Solution Architect","company":{"id":678956,"name":"MCA Connect","domain":"mcaconnect.com","url":"https://alion.io/company/mcaconnect","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Lever","truth_index":null},"role":"Solutions","role_family":"Solutions","seniority":"lead","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":180000,"max":240000,"currency":"USD","period":"year","gross":null,"usd_annual":240000},"salary_estimate":null,"experience_years_min":10,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Azure","optional":false},{"name":"Databricks","optional":false},{"name":"Machine Learning","optional":false},{"name":"OpenAI","optional":false},{"name":"Power BI","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"PyTorch C++","optional":false},{"name":"Spark","optional":false},{"name":"Time Series Forecasting","optional":false},{"name":"Transformers","optional":false},{"name":"C++","optional":true}],"status":"live","first_seen_at":"2026-09-25T19:10:22Z","employer_posted_date":"2026-09-25","last_verified_at":"2026-09-27T00:36:11Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Lead Data Scientist - Solution Architect\nLocation\nRemote with light travel as needed to client sites\nEmployment Type\nFull-time\nPosition Summary\nThe 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.\nIn 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.\nThe 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.\nKey Responsibilities\nSolution Architecture & Technical Leadership\nServe as the architectural lead for complex data science, AI, machine learning, forecasting, optimization, and advanced analytics engagements.\n\nPartner with clients to understand business challenges, gather requirements, identify data limitations, and translate business needs into scalable technical solutions.\n\nDesign 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.\n\nProvide technical direction on model design, algorithm selection, data preparation, feature engineering, training, validation, deployment, monitoring, and optimization.\n\nEvaluate and recommend appropriate modeling approaches, including regression techniques, forecasting models, deep learning methods, optimization algorithms, and advanced statistical approaches.\n\nLead architecture decisions related to compute configuration, GPU acceleration, model performance, scalability, deployment patterns, and Azure cost/performance optimization.\n\nEnsure solutions are designed for long-term maintainability, scalability, observability, and business value.\n\nStay current with emerging Microsoft data, AI, and agent technologies, including Azure AI Foundry, M365 Agents, Azure OpenAI, and related tools.\n\nAct as a subject matter expert for internal teams and clients on data science architecture, AI strategy, machine learning engineering, and advanced analytics delivery.\n\nDelivery & Client Engagement\nLead client-facing discovery and requirement gathering sessions to define project goals, business outcomes, technical requirements, and success measures.\n\nWork directly with customers to understand business processes, analytical needs, data maturity, and operational constraints.\n\nGuide project teams through ambiguous, incomplete, or messy data environments by diagnosing issues, proposing solutions, and escalating appropriately when needed.\n\nCommunicate complex analytical and technical concepts clearly to both technical teams and business stakeholders.\n\nDeliver actionable recommendations that help clients understand model outputs, business implications, risks, limitations, and opportunities for improvement.\n\nSupport the development of Statements of Work, proposals, solution estimates, technical approach documentation, and project plans as needed.\n\nCollaborate with data engineers, data architects, project managers, business analysts, and client stakeholders to ensure successful end-to-end delivery.\n\nEnsure data science solutions align to client goals, MCA delivery standards, Microsoft best practices, and long-term supportability.\n\nPeople Management & Mentorship\nDirectly manage, mentor, and support a Senior Data Scientist Consultant.\n\nProvide regular coaching, feedback, and technical guidance to support professional growth and project success.\n\nReview technical deliverables, model design decisions, code quality, documentation, and client-facing outputs.\n\nHelp prioritize work, remove blockers, and ensure the Senior Data Scientist Consultant is aligned to project goals and client expectations.\n\nSupport performance management, goal setting, skills development, and career growth for direct report(s).\n\nFoster a collaborative, curious, and high-accountability team culture.\n\nPartner with Data & AI leadership to identify opportunities for team improvement, knowledge sharing, reusable assets, and delivery process enhancements.\n\nData Science, AI & Machine Learning Expertise\nBuild, review, and guide the development of predictive models, statistical models, optimization models, forecasting solutions, and other analytical applications.\n\nApply advanced statistical and machine learning methods to large, complex structured and unstructured datasets.\n\nUse Python as the primary programming language for model development, data exploration, experimentation, and production-ready analytical solutions.\n\nWork with Spark and large-scale data processing frameworks to support high-volume analytics and machine learning workloads.\n\nDevelop and evaluate deep learning models using PyTorch.\n\nApply and explain multiple regression techniques, time-series approaches, and forecasting models.\n\nWork with algorithms and methods such as ARIMA, TBATS, Temporal Fusion Transformer, Prophet, and other relevant forecasting or optimization techniques.\n\nSupport production model deployment, monitoring, drift detection, availability, and performance measurement.\n\nLead experimentation and model validation processes to ensure solutions are accurate, explainable, and aligned with business outcomes.\n\nAvoid over-reliance on AutoML by demonstrating hands-on coding ability, critical thinking, and strong foundational understanding of machine learning and statistical methods.\n\nRequired Qualifications\n10+ years of hands-on experience in data science, machine learning, AI, advanced analytics, or related technical disciplines.\n\nPrior experience in technical architecture, lead data scientist, principal data scientist, AI/ML architect, or similar senior-level role.\n\nStrong proficiency in Python for data science, machine learning, deep learning, statistical modeling, and production-level solutions.\n\nExperience with Spark and large-scale data processing.\n\nStrong experience with Azure-based data and AI technologies, including Azure Machine Learning and related Azure data services.\n\nExperience with Azure AI Foundry, Azure OpenAI, Azure AI Search, M365 Agents, or similar AI/agent frameworks.\n\nHands-on experience with PyTorch for deep learning model development.\n\nStrong foundation in statistics, regression, forecasting, optimization, and machine learning methodology.\n\nExperience developing, deploying, owning, and monitoring production-level machine learning models.\n\nAbility to evaluate and apply time-series and forecasting techniques such as ARIMA, TBATS, Temporal Fusion Transformer, Prophet, or similar methods.\n\nExperience working with structured, semi-structured, and unstructured data.\n\nExperience connecting to and working with data platforms such as data lakes, data warehouses, APIs, NoSQL databases, and cloud-native data services.\n\nAbility to translate business needs into technical requirements through active partnership with clients, stakeholders, data scientists, data engineers, and data architects.\n\nStrong communication and storytelling skills, with the ability to explain technical concepts and model outputs to non-technical audiences.\n\nDemonstrated ability to lead complex client-facing engagements and manage multiple priorities.\n\nStrong problem-solving mindset with curiosity, perseverance, and the ability to work through incomplete systems or ambiguous data challenges.\n\nExperience mentoring, coaching, or managing technical team members.\n\nMust be open to approximately 10% travel as needed.\n\nPreferred Qualifications\nMaster’s or Ph.D. in Computer Science, Statistics, Applied Mathematics, Data Science, Engineering, Operations Research, or a related field.\n\nStrong academic foundation in statistics, computer science, mathematics, optimization, or research-based analytical methods.\n\nPublished research, thesis work, National Academy of Sciences affiliation, or other demonstrated research depth.\n\nExperience in manufacturing, supply chain, demand forecasting, inventory optimization, quality analytics, production analytics, or industrial operations.\n\nExperience with cloud-native or ML-native organizations, research-heavy environments, or algorithmic optimization-focused teams.\n\nExperience with C++, GPU acceleration, distributed training, or compute optimization.\n\nExperience configuring Azure compute environments for machine learning performance, scalability, and cost efficiency.\n\nExperience with Databricks, Azure Databricks, or equivalent big data and ML engineering platforms.\n\nExperience supporting proposal development, solution estimation, technical sales support, or pre-sales activities.\n\nPrior consulting experience in a client-facing technical leadership role.\n\nIdeal Candidate Profile\nThe 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.\nThey 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.\nThis 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.","description_format":"text","description_chars":10595,"description_truncated":false,"requirements":{"experience_years_min":10,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"master","optional":false},"security_clearance":false,"languages":[]},"benefits":["Professional development"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Enterprise Apps Implementation Partners","Analytics & BI Consulting"],"lifecycle":[{"event":"open","at":"2026-09-26T01:52:11Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":0,"expected_fill_days":44,"reasons":["conf:3","velocity","win:early"],"computed_at":"2026-09-26T05:45:00Z"},"pay":{"stated_usd_annual":240000,"is_top_pay":true},"html_url":"https://alion.io/job/mca-connect-lead-data-scientist-solution-architect","json_url":"https://alion.io/job/mca-connect-lead-data-scientist-solution-architect.json","meta":{"generated_at":"2026-09-27T01:32:50Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1413,"day_limit":5000,"remaining_today":3587,"minute_limit":60,"resets_at":"2026-09-28T00:00:00Z"}}}