Data Scientist

Praise Tech Solutions; Northern (KY); Hybrid; USD 120,000 - 180,000; Full time

Job summary

Praise Tech Solutions is seeking a skilled machine learning engineer to design, train, and optimize models for predictive analytics across diverse datasets. The role emphasizes regression, classification, clustering, and deep learning architectures using TensorFlow, PyTorch, and Keras.

You will implement NLP models with GPT/BERT/T5, deploy on AWS/Azure, and build dashboards with Tableau/Power BI/D3.js, enabling data-driven decision making across teams.

Qualifications

• Experience designing and optimizing regression, classification, and clustering models.
• Proficient in NLP model development using transformers and modern frameworks.
• Strong data cleaning, normalization, encoding, and feature engineering skills.

Responsibilities

• Design, train, and optimize regression, classification, and clustering models to uncover patterns in complex datasets. Implement deep learning architectures using TensorFlow, PyTorch, Keras for predictive analytics
• Develop state-of-the-art NLP models using GPT, BERT, T5, and Hugging face transformers for tasks like text generation, summarization, and information retrieval
• Perform data cleaning, normalization, encoding, and dimensionality reduction to enhance model accuracy
• Deploy machine learning models on AWS and Azure. Implement containerized solutions using Docker and Kubernetes for scalable AI applications. Utilize serverless computing for efficient model execution
• Develop predictive models for fraud detection, risk assessment, and customer segmentation. Utilize graphic analytics for network-based insights
• Build interactive dashboard using Tableau, Power BI, or D3.js to communicate insights. Automate report generation with Python, R, or SQL.
• Work closely with cross-functional teams to integrate AI-driven solutions into business workflows. Communicate technical concepts effectively to nontechnical stakeholders. Drive data-driven strategies to optimize decision making

Skills

Regression modeling

Classification

Clustering

Deep learning

NLP models

GPT/BERT/T5

TensorFlow

PyTorch

Keras

AWS

Azure

Docker

Kubernetes

Tableau

Power BI

D3.js

Python

R

SQL

Feature engineering

Tools

Docker

Kubernetes

AWS

Azure

Tableau

Power BI

D3.js

Job description

Job Duties

• Design, train, and optimize regression, classification, and clustering models to uncover patterns in complex datasets. Implement deep learning architectures using TensorFlow, PyTorch, Keras for predictive analytics
• Develop state-of-the-art NLP models using GPT, BERT, T5, and Hugging face transformers for tasks like text generation, summarization, and information retrieval
• Perform data cleaning, normalization, encoding, and dimensionality
• reduction to enhance model accuracy. Engineer custom features to improve predictive performance in applications. Optimize data pipelines for real-time processing and large-scale analytics
• Deploy machine learning models on AWS and Azure. Implement containerized solutions using Docker and Kubernetes for scalable AI applications. Utilize serverless computing for efficient model execution
• Develop predictive models for fraud detection, risk assessment, and customer segmentation. Utilize graphic analytics for network-based insights
• Build interactive dashboard using Tableau, Power BI, or D3.js to communicate insights. Automate report generation with Python, R, or SQL.
• Work closely with cross-functional teams to integrate AI-driven solutions into business workflows. Communicate technical concepts effectively to nontechnical stakeholders. Drive data-driven strategies to optimize decision making

Location: Anywhere in USA