Machine Learning Engineer/Data Scientist

A Day in Life:

• Detailed documentation including conceptual design, logical design, physical design, bill of materials, as-built diagrams, knowledge transfer materials, FAQs, transition to operations information
• Being one of the few trusted advisors for clients, building long-term relationships that will further business value
• Attending and representing Long View at the latest industry events
• Lead discovery to translate business goals into well‑scoped analytical problems, measurable KPIs, and model success criteria
• Build reproducible experiments and models (classification, regression, forecasting, NLP/LLMs) using Python and Azure ML/Databricks, document assumptions and limitations.
• Engineer and select features; perform rigorous validation (cross‑validation, leakage checks), bias/variance trade‑off, and error analysis; apply Responsible AI practices.
• Partner with ML Engineers for operational models with CI/CD, experiment tracking (ML flow), model registries, and online/offline evaluation pipelines.
• Design and evaluate GenAI use cases when relevant (prompt engineering, evaluation harnesses, RAG with Azure AI Search, grounded generation, safety testing).
• Communicate results and trade‑offs to non‑technical stakeholders; create compelling visuals and narratives; facilitate decisions that balance accuracy, cost, and operational risk.
• Architect and implement ML platforms and pipelines in Azure (Azure Machine Learning, Azure Databricks, Azure Synapse/Microsoft Fabric, Azure Data Lake Storage, Event/Service Bus).
• Participate in discovery workshops, solution estimation, Statements of Work inputs, and stakeholder demos; produce clear design docs, runbooks, and handover materials.
• Carry a mobile phone for client and / or for Long View Systems support
• Track personal time billings and report them in a timely manner.
• Attend a quarterly Career Life Planning session with your Team Lead or Manager to discuss your interests, training opportunities, your utilization, and other exciting topic
• Contribute to various government audits and special programs that Long View participates in every year. Part of your duties will be to participate in these programs where needed as they relate to your technology area(s).
• Attending and representing Long View at the latest industry events 

What You Bring:

• A minimum of 5-6 years in applied data science/analytics with shipped models impacting business KPIs.
• Experience with Python, statistical modeling, experiment design, and ML techniques (tree‑based methods, GLMs, time‑series, causal inference basics).
• Experience with Azure ML, Databricks/Spark, SQL, and data wrangling at scale; familiarity with Fabric/Synapse data pipelines.
• Strong MLOps collaboration (MLflow, model lifecycle, monitoring/alerts, data quality checks such as Great Expectations equivalent patterns).
• Exceptional customer engagement, interpersonal, stakeholder facilitation, presentation and overall communication skills
• Consulting experience.
• Good understanding of ITIL Incident Management
• Excellent problem‑solving and multitasking skills.

What Makes You Extra Awesome:

• Certifications: DP‑100, DP‑203, AI‑102, AZ‑900/AI‑900
• Experience with NLP/LLMs and RAG on Azure
• Probabilistic modeling; optimization, Bayesian methods, A‑B testing at scale
• Experience in supply chain analytics or inventory optimization