Lead Data Scientist – Solution Architect

🕒 vor 25 Tagen

🇺🇸 Vereinigte Staaten – Remote

💵 $180.000 - $240.000 / Jahr

⏰ Vollzeit

🟠 Senior

💻 Lösungsingenieur

👻 Geisterscore 2%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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Lebenslauf hochladen

MCA Connect

WebsiteLinkedInAlle Stellen

201 - 500 Mitarbeiter

🏥 Gesundheitswesen

📦 Logistik

💼 Beratung

💰 Private Equity Round im 2020-07

Healthcare • Logistics • Consulting

Durch Leidenschaft und tiefes Branchen-Know-how hilft MCA Connect Herstellern, erfolgreich zu sein, indem es Innovation durch umsetzbare Geschäftseinblicke freisetzt.

Beschreibung

• 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

🎯 Anforderungen

• 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

🏖️ Vorteile

• 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