Technical Lead - Dallas, United States - iLink Digital

Description

Dallas, United States | Posted on 04/18/2024iLink is a GlobalSoftware Solution Provider and Systems Integrator, deliversnext-generation technology solutions to help clients solvecomplex business challenges, improve organizationaleffectiveness, increase business productivity, realizesustainable enterprise value and transform your businessinside-out.

iLink integrates software systems and developscustom applications, components, and frameworks on the latestplatforms for IT departments, commercial accounts, applicationservices providers (ASP) and independent software vendors(ISV).

iLink solutions are used in a broad range of industriesand functions, including healthcare, telecom, government, oiland gas, education, and life sciences.

iLinks expertiseincludes Cloud Computing & Application Modernization, DataManagement & Analytics, Enterprise Mobility, Portal,collaboration & Social Employee Engagement, EmbeddedSystems and User Experience designetc.

What makes iLinkSystems' offerings unique is the fact that we usepre-created frameworks, designed to accelerate softwaredevelopment and implementation of business processes for ourclients.

iLink has over 60 frameworks (solution accelerators),both industry-specific and horizontal, that can be easilycustomized and enhanced to meet your current businesschallenges.

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.

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.
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 understandrequirements 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.
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.

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