We are looking for an experienced Data Scientist / AI ML Engineer to join an exciting project based in Mason, OH. The ideal candidate will have 10+ years of experience in Data Science, with a strong background in Artificial Intelligence (AI), Machine Learning (ML), and Natural Language Processing (NLP). This is an onsite role, requiring presence at the Mason, OH location.
The selected candidate will work closely with cross-functional teams to design, develop, and deploy AI/ML models that drive key business decisions and innovation.
Key Responsibilities:
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Develop and implement AI/ML models to solve complex business problems using advanced techniques such as NLP, Deep Learning, and Reinforcement Learning.
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Work with large datasets and design solutions that involve data wrangling, preprocessing, and feature engineering.
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Analyze and interpret complex data to identify trends, patterns, and insights that drive business decisions.
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Collaborate with data engineers, product managers, and business stakeholders to understand requirements and deliver AI/ML-driven solutions.
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Design and implement algorithms for Natural Language Processing (NLP) and Large Language Models (LLMs) to support business use cases.
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Apply knowledge of data structures and data modeling to organize and analyze large-scale data.
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Optimize and fine-tune machine learning models for accuracy, scalability, and performance.
- Document processes, workflows, and model development for future reference and reproducibility.
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Stay current with the latest advancements in AI, ML, NLP, and Data Science techniques.
Mandatory Skills & Qualifications:
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10+ years of experience in Data Science, with hands-on experience in AI and ML applications.
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Proficiency in Python, with expertise in libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, or PyTorch.
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Deep knowledge and hands-on experience in Artificial Intelligence (AI) and Machine Learning (ML) techniques such as Supervised/Unsupervised Learning, Deep Learning, and Reinforcement Learning.
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Experience working with Natural Language Processing (NLP) techniques and frameworks like spaCy, NLTK, Transformers, etc.
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Familiarity with Large Language Models (LLM) such as GPT-3, BERT, or similar technologies.
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Strong understanding of data structures, data modeling, and database management.
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Experience in building, testing, and deploying machine learning models.
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Solid understanding of statistics and mathematical modeling for AI/ML applications.
- Strong problem-solving skills and the ability to translate business needs into technical requirements.
- Excellent communication skills with the ability to present complex findings to non-technical stakeholders.