iLink Digital

iLink is a Global Software Solution Provider and Systems Integrator, delivers next-generation technology solutions to help clients solve complex business challenges, improve organizational effectiveness, increase business productivity, realize sustainable enterprise value and transform your business inside-out.. iLink’s expertise includes Cloud Computing & Application Modernization, Data Management & Analytics, Enterprise Mobility, Portal, collaboration & Social Employee Engagement, Embedded Systems and User Experience design etc.. As a Technical Lead, you will play a pivotal role in driving the development and deployment of machine learning models based on electronic health records (EHR) information.. Utilize Natural Language Processing (NLP) techniques, including tools such as SpaCy and NER (Named Entity Recognition), to extract insights from unstructured EHR data.. Proficiency in machine learning tools and libraries such as SpaCy, TensorFlow, PyTorch, scikit-learn, and Azure ML.

technical lead

About The Company:




iLink is a Global Software Solution Provider and Systems Integrator, delivers next-generation technology solutions to help clients solve complex business challenges, improve organizational effectiveness, increase business productivity, realize sustainable enterprise value and transform your business inside-out. iLink integrates software systems and develops custom applications, components, and frameworks on the latest platforms for IT departments, commercial accounts, application services providers (ASP) and independent software vendors (ISV). iLink solutions are used in a broad range of industries and functions, including healthcare, telecom, government, oil and gas, education, and life sciences. iLink’s expertise includes Cloud Computing & Application Modernization, Data Management & Analytics, Enterprise Mobility, Portal, collaboration & Social Employee Engagement, Embedded Systems and User Experience design etc.




What makes iLink Systems' offerings unique is the fact that we use pre-created frameworks, designed to accelerate software development and implementation of business processes for our clients. iLink has over 60 frameworks (solution accelerators), both industry-specific and horizontal, that can be easily customized and enhanced to meet your current business challenges.





Requirements
Job Description:




We are seeking an experienced and highly skilled Technical Lead in Machine Learning and Data Science to join our team. As a Technical Lead, you will play a pivotal role in driving the development and deployment of machine learning models based on electronic health records (EHR) information. Your responsibilities will include leading the data science team, collaborating with stakeholders, and ensuring successful production deployment of machine learning models in the Azure cloud environment.

Key Responsibilities:

1. Leadership and Team Management:

Lead and mentor a team of data scientists and machine learning engineers.

Define project goals, timelines, and deliverables, and ensure they are met.

Foster a culture of collaboration, innovation, and continuous learning within the team.

2. Machine Learning Model Development:

Utilize Natural Language Processing (NLP) techniques, including tools such as SpaCy and NER (Named Entity Recognition), to extract insights from unstructured EHR data.

Develop and implement classification algorithms for categorizing EHR information.

Build topic modeling classifiers to identify key themes and trends in healthcare data.

Utilize Deep Learning techniques for advanced data analysis and prediction.

3. Azure Cloud Deployment:

Work closely with Azure ML Workbench to develop, test, and deploy machine learning models in the Azure cloud environment.

Implement scalable and reliable production pipelines for model deployment and monitoring.

Collaborate with DevOps teams to ensure smooth integration of machine learning models into existing healthcare systems.

4. Performance Optimization and Model Evaluation:

Optimize machine learning models for performance, scalability, and accuracy.

Conduct rigorous testing and validation to ensure the quality of deployed models.

Monitor model performance in production and implement improvements as needed.

5. Stakeholder Collaboration:

Collaborate with healthcare professionals, data analysts, and business stakeholders to understand requirements and goals.

Translate business needs into technical solutions and actionable insights.

Qualifications:

Master's or Ph.D. in Computer Science, Data Science, Statistics, or a related field.

10+ years of experience in data science, machine learning, and AI.

Strong expertise in NLP techniques, including text preprocessing, entity recognition, and sentiment analysis.

Proficiency in machine learning tools and libraries such as SpaCy, TensorFlow, PyTorch, scikit-learn, and Azure ML.

Experience building and deploying machine learning models in the Azure cloud environment.

Familiarity with DevOps practices and tools for continuous integration and deployment (CI/CD).

Excellent problem-solving skills and the ability to work in a fast-paced, collaborative environment.

Strong communication and leadership skills, with a track record of successfully leading data science projects from conception to production.

Benefits:

Competitive salary and benefits package.

Opportunities for professional growth and development.

Collaborative and innovative work environment.

Impactful work in the healthcare analytics domain, contributing to improved patient outcomes and healthcare delivery.

If you meet the qualifications and are passionate about leveraging machine learning and data science to make a difference in healthcare, we encourage you to apply for this exciting opportunity.

Benefits
Competitive salaries

Medical, Dental, Vision Insurance

Disability, Life & AD&D Insurance

401K With Generous Company Match

Paid Vacation and Personal Leave

Pre-Paid Commute Options

Employee Referral Bonuses

Performance Based Bonuses

Flexible Work Options & Fun Culture

Continuing Education Reimbursements

In-House Technology Training


Industry
IT Services
State/Province
Texas
City
Dallas
Zip/Postal Code
75203
Country
United States

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