Data Scientist

Lorven Technologies Inc

Cary, NC, United States

10 days ago

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

5 years minimum

Working hours

Regular working hours

Job source

www.careerjet.com

Tech stack

Application Programming Interfaces (APIs) Artificial Intelligence Data Analysis Microsoft Azure Batch Processing Big Data Business Software Cloud Computing Data Validation Monitoring of Systems Python (Programming Language) Machine Learning

+8 more

Power BI Standard Sql Azure Machine Learning Feature Engineering Model Validation Generative AI Machine Learning Operations Microservices

Job description

Design, develop, train, optimize, and deploy Machine Learning and AI models for marketing, customer engagement, and business intelligence use cases.
Analyze complex datasets to identify trends, patterns, and actionable insights that drive business strategies and revenue growth.
Develop predictive models and AI solutions to improve customer experience, campaign effectiveness, communication strategies, and business outcomes.
Build and integrate AI capabilities into business applications through APIs, SDKs, microservices, and cloud-based solutions.
Perform statistical analysis, data exploration, feature engineering, and model evaluation to improve prediction accuracy and performance.
Collaborate with business stakeholders, data engineers, analysts, and cross-functional teams to deliver scalable AI-driven solutions.
Create dashboards, visualizations, reports, and presentations to communicate insights and recommendations to leadership teams.
Support ML platform optimization, scalability, reliability, and production stability through MLOps best practices.
Stay current with emerging AI, Machine Learning, Generative AI, and cloud technologies to drive innovation.

Requirements

8+ years of hands-on experience in Data Science, Artificial Intelligence, and Machine Learning engineering.
Strong experience designing, developing, deploying, and supporting production-grade Machine Learning and GenAI solutions.
5+ years of experience in insurance, financial services, or related industries with exposure to sales, marketing, customer engagement, and business analytics.
Strong proficiency in Python for Machine Learning, predictive modeling, statistical analysis, and AI solution development.
Experience building and deploying ML models using cloud platforms, preferably Microsoft Azure and Azure Machine Learning.
Strong knowledge of SQL, data analysis, Exploratory Data Analysis (EDA), data validation, anomaly detection, and large-scale data processing.
Experience with ML deployment practices including APIs, batch processing, real-time inference, model monitoring, and MLOps best practices.
Hands-on experience with tools such as Domino Data Lab (Domino), Power BI, Azure ML, and other data science platforms.
Strong understanding of responsible AI practices including data privacy, bias mitigation, model governance, and monitoring.
Excellent communication and presentation skills with the ability to translate complex data insights into business recommendations.