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NucleusTeq

AI-driven enterprise software and data modernization

Data Scientist

Project ManagementConfirmed live in the last 24 hours
Full-timePhoenix, AZ, USANo salary listed

About the Job

Requirements

  • A Master’s Degree in Data Analytics is required.
  • At least 6 months of experience is required.
  • Experience as a Deputy Manager is acceptable, or an equivalent combination of education, training, or experience.

Responsibilities

  • Develop and manage project roadmaps for artificial intelligence 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 and machine learning models and integrate them into production environments.
  • Collaborate with stakeholders to define AI, machine learning, and data product requirements aligned with business goals and project objectives for large-scale data solutions.
  • Oversee the development, testing, and deployment of AI and machine learning models to meet performance, accuracy, and scalability requirements.
  • Ensure effective data collection, cleaning, and transformation processes, applying data governance best practices so models are built on high-quality, structured data.
  • Monitor and evaluate AI and machine learning model performance using metrics such as accuracy, precision, recall, and F1-score, and adjust models based on feedback and performance reports.
  • Oversee the integration and deployment of large language models such as GPT and BERT into products for natural language processing tasks including sentiment analysis, chatbots, and customer service automation.
  • Implement Agile Scrum or Kanban methodologies for AI and machine learning projects, supporting iterative development and continuous delivery of AI-driven features.
  • Perform exploratory data analysis on large datasets to identify trends, patterns, and insights that inform model development and data-driven decisions.
  • Act as the primary stakeholder contact, provide regular project updates, and translate complex technical data into business-friendly insights.
  • Identify and manage risks related to AI and machine learning model deployment, including data quality issues, model performance degradation, and algorithmic bias.
  • Implement monitoring frameworks to evaluate real-world model performance after deployment and ensure models adapt based on new data and user feedback.
  • Ensure AI and machine learning models comply with industry regulations and ethical guidelines, including data privacy, bias mitigation, and transparency in decision-making.
  • Use data analysis and model insights to recommend product enhancements and optimizations that improve user experience and business outcomes.
  • Provide mentorship to junior team members on AI and machine learning concepts, model-development best practices, and data-engineering techniques.

About the Company

NucleusTeq

AI-driven enterprise software and data modernization

NucleusTeq delivers AI-powered software services and products to large enterprises, focusing on data modernization, cloud migration, and enterprise automation. Its flagship NuoData platform provides end-to-end data modernization, governance, and analytics to reduce integration costs and simplify data management. The company distinguishes itself through partnerships with AWS, Google Cloud, Microsoft Azure, and Snowflake, plus an experienced leadership team and a global delivery network. Its goal is to help Fortune 500 and 1000 firms upgrade legacy systems and speed digital transformation using AI-driven solutions.

Company size
201-500
Company stage
Not listed
Total funding
Not listed
Headquarters
Phoenix, AZ
Founded
2018

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