Data Scientist

NucleusTeq; Phoenix, Northern (AZ, KY); Hybrid; USD 110,000 - 160,000; Full time

Job summary

NucleusTeq is seeking a Data Scientist (internal title: Technical Project Manager) to drive the development of NuoData, an AI-powered data management platform. You will lead roadmaps for AI/ML products and coordinate data scientists, engineers, and designers to deliver features at scale.

The ideal candidate has a Master’s in Data Analytics and at least 6 months in related roles, with strong data governance, NLP/LLM deployment, and agile project management experience.

Qualifications

• Master's degree in Data Analytics or equivalent required.
• 6 months of experience acceptable in related roles.
• Experience leading AI/ML projects and data products is preferred.

Responsibilities

• Develop and manage AI/ML product roadmaps and features.
• Lead cross-functional teams for AI/ML model deployment.
• Define AI/ML requirements with stakeholders to meet business goals.
• Oversee development, testing, and deployment of models for performance.
• Ensure data collection, cleaning, and governance for high-quality data.
• Mentor junior team members on AI/ML concepts and techniques.
• Identify and manage deployment risks and post-deployment monitoring.
• Provide regular updates on progress to stakeholders.

Skills

Project management

Data analysis

Cross-functional collaboration

Agile frameworks

Education

Master's degree in Data Analytics

Tools

Python

SQL

ML frameworks

Job description

JOB INFORMATION

Job Title of Opening: Data Scientist

Position is for a Data Scientist (internal title: Technical Project Manager) responsible for the development of NuoData, which is an AI powered data management platform that is proprietary to NucleusTeq, Inc. Duties include, but are not limited to: Develop and manage project roadmaps for AI and Machine Learning-driven products, ensuring timely delivery of features that leverage large-scale data models and AI systems; Lead cross-functional teams of data scientists, engineers, and designers to implement AI/ML models, ensuring seamless integration into production environments; Collaborate with stakeholders to define AI/ML and data product requirements, ensuring alignment with business goals and project objectives for large-scale data solutions; Oversee the development, testing, and deployment of AI and machine learning models, ensuring that models meet performance, accuracy, and scalability requirements; Ensure effective data collection, cleaning, and transformation processes, applying best practices in data governance to ensure that AI and ML models are built on high-quality, structured data;

Continuously monitor and evaluate the performance of AI/ML models using appropriate metrics (e.g., accuracy, precision, recall, F1-score) and adjust models as needed based on

feedback and performance reports; Oversee the integration and deployment of LLMs (e.g., GPT, BERT) into products for NLP tasks such as sentiment analysis, chatbots, and customer service automation; Implement Agile Scrum or Kanban methodologies for AI/ML projects, ensuring iterative and incremental development of machine learning models, and continuous delivery of AI-driven features; Perform exploratory data analysis (EDA) on large datasets to identify trends, patterns, and insights that inform AI model development and data-driven decision-making; Act as the primary point of contact for stakeholders, providing regular updates on the progress of AI/ML projects and translating complex technical data into business friendly insights; Proactively identify and manage risks related to the deployment of AI/ML models, such as data quality issues, model performance degradation, and biases in AI algorithms; Implement monitoring frameworks to evaluate the real-world performance of AI/ML models post-deployment, ensuring models adapt and evolve based on new data and user feedback; Ensure AI/ML models comply with industry regulations and ethical guidelines, managing data privacy, bias mitigation, and transparency in model decision-making processes; Use insights from data analysis and AI models to recommend product enhancements and optimizations, leading to improved user experience and business outcomes; and provide mentorship to junior team members on AI/ML concepts, best practices for model development, and data engineering techniques.

Requires a Master’s Degree in Data Analytics and 6 months of experience. Experience as a Deputy Manager is acceptable, or any suitable combination of education, training or experience thereof.

Job Site: Employee is permitted to work remotely from his or her home residence, but will at times be required to travel to various unanticipated jobsites within the United States.