Technical Lead — Artificial Intelligence & Analytics (AIA)

BST Consultants, Inc.; Tampa (FL); Hybrid; USD 120,000 - 150,000; Full time

Job summary

A leading technology consulting firm is seeking a Technical Lead for AI & Analytics to manage a team of data scientists and engineers. The successful candidate will drive machine learning projects and oversee the development of data pipelines, primarily using Microsoft Azure and Fabric. This role requires strong expertise in machine learning architectures and data engineering practices, alongside proven team leadership. This position offers remote or hybrid flexibility for those located in the Tampa office.

Qualifications

• Deep knowledge of machine learning model architecture including supervised and unsupervised learning.
• Expert-level understanding of ETL/ELT pipelines and data warehousing.
• Seven or more years of experience in data engineering and/or data science.

Responsibilities

• Lead and mentor a team of data scientists and engineers in machine learning projects.
• Manage stakeholder expectations by communicating project progress.
• Drive the end-to-end ML lifecycle from feature engineering to model monitoring.

Skills

Machine Learning expertise

Python programming

Data Engineering proficiency

Stakeholder management

Problem-solving skills

Education

Bachelor's degree in relevant field

Master's degree preferred

Tools

Databricks

Apache Airflow

Microsoft Fabric Data Factory

Azure

Job description

Technical Lead—Artificial Intelligence & Analytics (AIA)

Department

• Data Science & Data Engineering Leadership

Location

• Remote/hybrid if located in Tampa, FL office

Summary of Duties & Responsibilities

As a Technical Lead—AI & Analytics at BST Global, you will lead a team of data scientists and data engineers in the design, development, and delivery of machine learning models, data pipelines and analytics products built on Microsoft Azure and Fabric. This role requires deep expertise in ML model architecture and design, data engineering, and proven team leadership skills, including holding staff accountable for deliverables, providing constructive feedback, monitoring work assignments and managing stakeholder expectations.

What You’ll Do

• Lead, mentor, and coach a cross‑functional team of data scientists and data engineers; monitor work assignments, track milestones, and hold staff accountable for the quality and timeliness of deliverables
• Manage stakeholder expectations by proactively communicating progress, risks, and trade‑offs to technical and non‑technical audiences
• Drive the end‑to‑end ML lifecycle, including feature engineering, model architecture and design, training, validation, deployment and monitoring
• Provide technical guidance on ML model selection, hyperparameter tuning and evaluation metrics; oversee predictive analytics solutions for project management data
• Architect scalable, resilient data pipelines using Databricks, Apache Airflow, Microsoft Fabric Data Factory and Microsoft Fabric; lead data modeling and warehousing efforts leveraging medallion architecture and Microsoft Fabric Lakehouse
• Establish and enforce engineering standards for ETL/ELT processes, code quality, version control, CI/CD, and security, including row‑level and object‑level controls
• Participate in and lead agile ceremonies; accurately estimate assignments and maintain technical documentation
• Evaluate emerging AI/ML frameworks and data engineering tools, making recommendations that advance team capabilities
• Assist with interviewing and onboarding new team members to ensure team sustainability

What We’re Looking For

• Data Science & ML Expertise: Deep knowledge of ML model architecture and design, including supervised and unsupervised learning, deep learning, NLP, and time‑series forecasting; prior experience leading data science teams and translating business problems into analytical solutions
• Data Engineering Proficiency: Expert‑level understanding of ETL/ELT pipelines, data warehousing, medallion architecture and orchestration tools; prior experience leading data engineering teams building enterprise‑scale data platforms
• Leadership & Accountability: Proven ability to set clear expectations, monitor deliverables, provide constructive feedback and hold team members accountable; skilled at managing stakeholder expectations across technical and business audiences
• Problem‑Solving & Communication: Strong analytical skills, with the ability to break down complex problems and develop effective solutions; effective at articulating ideas and collaborating across cross‑functional teams

Required Technical Skills

• Programming: Python (expert), T‑SQL (advanced), Spark/PySpark (advanced)
• ML & Data Science: ML model architecture and design (advanced); model training, validation and deployment (advanced); feature engineering
• Platforms & Tools: Databricks (advanced), Apache Airflow (advanced), Microsoft Fabric Data Factory (required); Microsoft Fabric, including Lakehouse, OneLake and semantic models (advanced)
• Cloud & Security: Azure compute, storage, databases and developer tools (advanced); row‑level and object‑level security; performance monitoring and optimization

Desired Skills

• Cross‑tenant data sharing and Microsoft Power BI/semantic model sharing in Microsoft Fabric
• Observability tooling and platform monitoring
• Knowledge of project management and financial concepts, including budgets, revenue, profit and earned value
• Certifications in Microsoft Azure, Python, SQL or Databricks

Education & Experience

• Bachelor’s degree in computer science, data science, statistics, mathematics or a related field; master’s degree preferred
• Seven or more years of experience in data engineering and/or data science with at least three years in a technical leadership role overseeing cross‑functional data teams

Number Supervised

5 – 10 data scientists and data engineers

Travel

Up to 5%

Classification

Exempt

Work Environment & Physical Demands

This job operates in a professional office environment with standard office equipment. Remote work is supported with core hours of 9:00 a.m. – 6:00 p.m. ET. The employee is regularly required to speak and listen and frequently required to stand, walk and use their hands.