Data Scientist

Job Duties: Develop and implement a set of techniques or analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualization software. Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets. Visualize, interpret, and report data findings. May create dynamic data reports.

Perform analysis on large datasets and produce qualitative visualizations based on reporting requirements. Develop analytical solutions and dashboards that integrate data from a wide variety of sources such as relational databases, AWS, data virtualization tools. Build statistical models (predictive and descriptive) for customer demand, satisfaction, sentiment and segmentation. Design experiments to test for hypotheses and answer business questions. Develop and deploy machine learning models. Understand technology operations data from many different sources in detail to create these models. Optimize workflows and scripts on data lake for data cleaning, processing and transformation. Collaborate with the engineering team to create, maintain and enhance data pipelines which gather data from various systems or sources. Partner closely with service managers and engineers to understand the underlying data and help them make business decisions through insights and data products.

Minimum Requirements: Master’s degree in Data/Information Science, Data/Business Analytics, Machine Learning or related field and three (3) years of experience in the job offered or in a data/software engineer-related occupation.

Some telecommuting is permitted.

Special Requirements: Position requires at least one (1) academic semester of graduate-level coursework or some experience in each of the following skills:

1. Utilize knowledge of Python and SQL to clean, transform, and analyze large-scale datasets, employing data visualization tools like Plotly and dashboarding tools like PowerBI, to effectively communicate actionable insights that enhance business processes and workplace productivity.
2. Utilize knowledge of data science, machine learning algorithms, and statistics to perform exploratory data analyses (EDA), design experiments, conduct hypothesis testing, and to build and interpret predictive models for data-driven decision-making.
3. Utilize knowledge of Natural Language Processing (NLP) techniques to pre-process text data, extract and analyze insights, and either present those insights directly to stakeholders or leverage the processed data to power downstream tasks driven by Large Language Models (LLMs).
4. Utilize knowledge of AWS and Azure cloud environments to design, deploy, and scale data pipelines and machine learning applications efficiently.
5. Utilize knowledge of AI/NLP and Large Language Models (LLMs) to design, develop, and optimize generative AI systems that manage prompts, memory, tools, and system behavior, leveraging frameworks such as LangChain and Hugging Face Transformers.
6. Utilize knowledge of software engineering principles including modularity, abstraction, reusability, and maintainability, along with version control systems (e.g., Git) and CI/CD tools (e.g., Jenkins) to design, develop, test, and deploy production-grade software systems in cloud environments.

*The starting base salary range for this role is reflected above. Salary is one part of Autodesk’s competitive package. Offers are based on the candidate’s experience and geographic location.