Data Scientist

Dminds Solutions Inc.; Corpus Christi (TX); On-site; USD 90,000 - 140,000; Full time

Job summary

Dminds Solutions Inc. is seeking a seasoned Data Scientist/ML Engineer to design, train, and deploy ML/AI models addressing complex business problems in a corporate environment. You will build GenAI/LLM-based solutions and work with structured and unstructured data to extract actionable insights.

Responsibilities include NLP model development, RAG pipelines, prompt engineering, and production monitoring. Strong Python, ML libraries, and SQL skills are essential, with collaboration across data

Qualifications

• Strong experience as a Data Scientist / Machine Learning Engineer / AI Engineer.
• Hands-on experience with Python and data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of Machine Learning, Deep Learning, NLP, and statistical modeling.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.
• Experience working with structured and unstructured datasets.
• Strong SQL and data manipulation skills.
• Experience developing and deploying production-grade AI/ML solutions.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.

Responsibilities

• Develop, train, evaluate, and deploy ML/AI models to solve complex business problems.
• Design and implement Generative AI and LLM-based solutions for enterprise use cases.
• Work with structured and unstructured data to identify patterns, trends, and actionable insights.
• Develop NLP solutions using modern transformer-based and LLM technologies.
• Build and optimize prompts, embeddings, retrieval pipelines, and RAG (Retrieval-Augmented Generation) solutions.
• Evaluate LLM outputs for accuracy, relevance, reliability, and performance.
• Perform exploratory data analysis, feature engineering, model development, and statistical analysis.
• Collaborate with data engineers, software engineers, product teams, and business stakeholders to take AI solutions from concept through production.
• Develop model evaluation frameworks and monitor model performance in production.
• Apply appropriate machine learning, deep learning, and statistical techniques to business problems.
• Work with cloud-based AI/ML platforms and modern data technologies.
• Document models, methodologies, experiments, results, and technical recommendations.
• Stay current with emerging developments in Generative AI, LLMs, NLP, and machine learning and evaluate their applicability to enterprise solutions.

Skills

Data Scientist

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

NLP

LLMs

Prompt engineering

RAG

Vector databases

SQL

Production ML

Tools

TensorFlow

PyTorch

Jupyter

Job description

• Develop, train, evaluate, and deploy machine learning and AI models to solve complex business problems.
• Design and implement Generative AI and LLM-based solutions for enterprise use cases.
• Work with structured and unstructured data to identify patterns, trends, and actionable insights.
• Develop NLP solutions using modern transformer-based and LLM technologies.
• Build and optimize prompts, embeddings, retrieval pipelines, and RAG (Retrieval-Augmented Generation) solutions.
• Evaluate LLM outputs for accuracy, relevance, reliability, and performance.
• Perform exploratory data analysis, feature engineering, model development, and statistical analysis.
• Collaborate with data engineers, software engineers, product teams, and business stakeholders to take AI solutions from concept through production.
• Develop model evaluation frameworks and monitor model performance in production.
• Apply appropriate machine learning, deep learning, and statistical techniques to business problems.
• Work with cloud-based AI/ML platforms and modern data technologies.
• Document models, methodologies, experiments, results, and technical recommendations.
• Stay current with emerging developments in Generative AI, LLMs, NLP, and machine learning and evaluate their applicability to enterprise solutions.

Key Responsibilities

• Develop, train, evaluate, and deploy machine learning and AI models to solve complex business problems.
• Design and implement Generative AI and LLM-based solutions for enterprise use cases.
• Work with structured and unstructured data to identify patterns, trends, and actionable insights.
• Develop NLP solutions using modern transformer-based and LLM technologies.
• Build and optimize prompts, embeddings, retrieval pipelines, and RAG (Retrieval-Augmented Generation) solutions.
• Evaluate LLM outputs for accuracy, relevance, reliability, and performance.
• Perform exploratory data analysis, feature engineering, model development, and statistical analysis.
• Collaborate with data engineers, software engineers, product teams, and business stakeholders to take AI solutions from concept through production.
• Develop model evaluation frameworks and monitor model performance in production.
• Apply appropriate machine learning, deep learning, and statistical techniques to business problems.
• Work with cloud-based AI/ML platforms and modern data technologies.
• Document models, methodologies, experiments, results, and technical recommendations.
• Stay current with emerging developments in Generative AI, LLMs, NLP, and machine learning and evaluate their applicability to enterprise solutions.

Required Skills

• Strong experience as a Data Scientist / Machine Learning Engineer / AI Engineer.
• Strong hands-on experience with Python and common data science/ML libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of Machine Learning, Deep Learning, NLP, and statistical modeling.
• Hands-on experience with Generative AI and Large Language Models (LLMs).
• Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation.
• Experience working with structured and unstructured datasets.
• Strong SQL and data manipulation skills.
• Experience developing and deploying production-grade AI/ML solutions.
• Strong analytical and problem-solving skills.
• Excellent communication and collaboration skills.