What are the responsibilities and job description for the Data Scientist/Machine Learning Engineer position at Jobs via Dice?
Dice is the leading career destination for tech experts at every stage of their careers. Our client, Clover Solutions LLC, is seeking the following. Apply via Dice today!
Data Scientist/Machine Learning Engineer (Python, NLP, AWS)
Pittsburgh, PA
Overview / Summary
We are seeking a Machine Learning Engineer with strong expertise in Python, statistics, and machine learning lifecycle management. The role involves designing, developing, and deploying ML and deep learning models to solve business problems, while collaborating with cross-functional teams to deliver impactful solutions.
Key Responsibilities
Data Scientist/Machine Learning Engineer (Python, NLP, AWS)
Pittsburgh, PA
Overview / Summary
We are seeking a Machine Learning Engineer with strong expertise in Python, statistics, and machine learning lifecycle management. The role involves designing, developing, and deploying ML and deep learning models to solve business problems, while collaborating with cross-functional teams to deliver impactful solutions.
Key Responsibilities
- Comprehend business issues and propose valuable solutions
- Design factual, AI, and deep learning models to address business challenges
- Develop, train, and deploy statistical, machine learning, and deep learning models for production
- Identify available data sources and determine how to augment data effectively
- Develop innovative data visualizations using tools like d3.js and Dash/Plotly
- Map business needs to processes and conceptualize end-to-end solutions
- Collaborate with team members in an agile project delivery environment
- Strong proficiency in Python programming and ML lifecycle
- Practical experience in statistics and operations research methods
- Hands-on experience with frameworks/tools such as Flask, PySpark, PyTorch, and Streamlit
- Experience with AWS AI/ML services such as SageMaker, Canvas, and Bedrock
- Understanding of predictive modeling techniques including regression, XGBoost, random forest, GBM, neural networks, and SVM
- Proficiency in NLP techniques including RNN, LSTM, and attention-based models
- Experience working with NLP models from Stanford, IBM, Azure, or OpenAI
- Strong SQL skills for writing efficient data queries
- Experience with version control tools such as GitHub or Bitbucket
- Hands-on experience in model training and deployment
- Experience working in agile environments
- Strong analytical, problem-solving, and communication skills
- Ability to understand, articulate, and visualize business requirements
- Strong interpersonal skills and ability to work collaboratively in a team