Data and AI Practice Lead - Remote (Fulltime)

The Dignify Solutions, LLC; Jersey City (NJ); Remote; USD 150,000 - 200,000; Full time

Job summary

A leading company is seeking a Data and AI Practice Lead to drive data platform modernization and AI initiatives. The ideal candidate will have extensive experience in data science and machine learning, with a proven track record in leading projects and teams. You will be responsible for aligning the strategic roadmap with market trends and executing successful AI solutions in various industry verticals.

Qualifications

• 10-12+ years in data science, machine learning, or AI.
• 4-5 years as a data science practice leader.

Responsibilities

• Develop a strategic roadmap for data platform modernization.
• Lead successful projects and teams in system integration.

Skills

Data Science

Machine Learning

AI

Python

R

Education

Relevant Certifications in Data Science

Tools

TensorFlow

Job description

Data and AI Practice Lead - Remote (Fulltime)

• Develop and execute a strategic roadmap for data platform modernization and AI practice, aligning with the firm's overall objectives and market trends.
• Extensive experience (10-12+ years) in data science, machine learning, AI, or related domains, with a proven track record of leading successful projects and teams within a system integration context.
• Experience in at least one industry vertical such as Fintech, Life sciences & Healthcare, Manufacturing, or Energy & Utilities is a MUST, along with relevant certifications in data science, AI, or related fields.
• Deep working knowledge of Generative AI and latest market trends, with the ability to create a roadmap and vision for clients.
• 4-5 years of experience as a data science practice leader at Big 4 or boutique consulting firms.
• Experience in solutions architecture and technical domains such as AI/ML, multimodal ML, model evaluation, MLOps, MLSecOps, ML training, inference, data engineering, data science, and fine-tuning.
• Proficiency with advanced analytics tools (Python, R), applied mathematics, ML, Deep Learning frameworks (TensorFlow), and ML techniques (e.g., random forest, neural networks).
• Experience in deploying Machine Learning solutions using various models (e.g., Linear/Logistic Regression, Support Vector Machines, Deep Neural Networks).
• Experience developing AI and ML models in real-world environments and integrating these solutions into large-scale enterprise applications using cloud-native or hybrid technologies.