Gen AI Full Stack Developer

5 days ago

Atlanta, Georgia, United States Daniel Ernest Full time
Job Title: Gen AI Full Stack Developer

Daniel Ernest is seeking a highly skilled Gen AI Full Stack Developer to join their team. As a key member of the Data & AI Consulting firm, you will be responsible for developing and implementing statistical and machine learning models to solve business problems.

Key Responsibilities:
  • Assist in data collection, pre-processing, and cleaning to ensure data quality and usability for analysis.
  • Perform exploratory data analysis to identify patterns, trends, and relationships in the data.
  • Develop and implement statistical and machine learning models to solve business problems.
  • Document requirements, design, develop, test and implement Generative AI applications using Large Language Models, Lang chain frameworks.
  • Collaborate with senior data scientists to design and execute experiments, analyze results, and generate actionable insights.
  • Conduct data visualization to effectively communicate findings and present insights to stakeholders.
  • Assist in developing and maintaining data pipelines and workflows for data ingestion, transformation, and analysis.
  • Aid in deploying machine learning models into production environments, ensuring they run efficiently and reliably.
  • Engage in code review processes to ensure quality and adherence to best practices.
  • Regularly check data sources for integrity and accuracy.
  • Commitment to continuous learning and staying updated with advancements in data science and related fields.
  • Stay abreast of the latest data science techniques, tools, and methodologies, and apply them to enhance analytics capabilities.
  • Collaborate with data engineering and IT teams to ensure seamless integration and availability of data for analysis.
  • Contribute to the development and improvement of data science workflows and best practices.
  • Document and communicate the methodology, assumptions, and limitations of data models and analyses.
  • Adhere to Non-Disclosure agreement, non-compete and policies and procedures
  • Delivery quality work products on time
  • Communicate proactively work hours, availability, vacation time
  • Respond to requests and attend meetings regularly
  • Do not store code or other technical objects on laptop or outside of the companies environments
  • Demonstrate strong work ethics
  • Do not disclose confidential information to anyone outside the business
  • Demonstrate core values of respect for individual, honesty, integrity in time and expense reporting
  • Engage with the team proactively
  • Stay on Teams when you are working
  • Own and drive quality deliverables on time
  • Check-in code daily
  • Communicate status frequently, daily is preferable including activities completed, issues, risks, milestones etc.
  • Reach out when support is needed from the team
Qualifications:
  • Bachelor's or Master's degree in Data Science, Computer Science, Statistics, or a related field.
  • Strong understanding of data science concepts, statistical analysis, and machine learning algorithms.
  • Proficiency in programming languages such as Python or R for data manipulation, analysis, and modeling.
  • Familiarity with data visualization tools and libraries, such as Matplotlib or Tableau.
  • Experience with data preprocessing, feature engineering, and data cleaning techniques.
  • Basic knowledge of SQL for data querying and manipulation.
  • Strong problem-solving skills and ability to think analytically.
  • Excellent communication skills, with the ability to effectively present complex concepts and findings to non-technical stakeholders.
  • Ability to work collaboratively in a team environment and contribute to team goals.
  • Knowledge of cloud platforms, such as AWS or Azure, and experience working with big data technologies are desirable.
  • Familiarity with version control systems like Git and knowledge of software development practices is a plus
  • Basic Understanding of Machine Learning Operations (MLOps): Familiarity with the lifecycle of machine learning models from development to deployment and maintenance.
  • Knowledge of Data Ethics and Privacy: Understanding of data privacy laws (like GDPR) and ethical considerations in data science.
  • Adaptability to New Technologies: Ability to quickly learn and adapt to new data analysis tools and techniques as they emerge.
  • Critical Thinking: Ability to approach problems critically and propose innovative solutions.
  • Project Management Skills: Basic project management skills to manage tasks efficiently and meet deadlines.

Please ensure your CV has been updated to reflect the skills and experiences needed.

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