Autodesk Inc.-posted 21 days ago
Full-time • Mid Level
Remote • San Francisco, CA
5,001-10,000 employees
Publishing Industries

Work on a variety of problems that seek to better understand how customers use Autodesk products and what drives deeper adoption and usage of these products. Apply your quantitative analysis, data mining and knowledge of machine learning algorithms to build models that make sense of user needs, usage patterns, factors that drive deeper adoption and contribute to subscriber churn. As part of a technical team, actively work on the productization of machine learning pipelines i.e., define architecture and solutions for automating data extraction, data processing and the entire machine learning lifecycle; and actively participate in the maintenance and improvement of existing models/pipelines. Write algorithms to efficiently detect and analyze patterns in very large datasets in order to mine useful insights that could Influence product development, strategy and roadmap prioritization through the application of analysis. Leverage knowledge of the Data warehouse to develop dashboards and reports based on the analysis to convey insights to the stakeholders. Tackle complex problems requiring a creative mindset to find innovative and elegant solutions. Some telecommuting is permitted.

  • 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.
  • Actively work on the productization of machine learning pipelines i.e., define architecture and solutions for automating data extraction, data processing and the entire machine learning lifecycle; and actively participate in the maintenance and improvement of existing models/pipelines.
  • Write algorithms to efficiently detect and analyze patterns in very large datasets in order to mine useful insights that could Influence product development, strategy and roadmap prioritization through the application of analysis.
  • Leverage knowledge of the Data warehouse to develop dashboards and reports based on the analysis to convey insights to the stakeholders.
  • Tackle complex problems requiring a creative mindset to find innovative and elegant solutions.
  • Master's degree in Data/Business Analytics, Data/Computer Science, Engineering or related field and two (2) years of experience in the job offered or in a data science-related occupation.
  • Utilize knowledge of Data Mining & Machine Learning to create predictive models tailored to customers' business needs, enabling proactive decision-making.
  • Utilize knowledge of Data Science and Exploratory Data Analysis to understand customer's journey and identify areas for improvement.
  • Utilize knowledge of Python and Bash scripting for AI/ML process automation, workflow optimization, and application deployment.
  • Utilize knowledge of Deep Learning and Computer vision algorithms to automate manual processes, streamline operations, and improve efficiency of products that involve visual data (like images, videos) analysis.
  • Utilize knowledge of Big Data tools like AWS, PySpark, SQL to perform data analysis on large datasets.
  • Utilize knowledge of Airflow and AWS Glue to automate the extraction of data from various sources such as databases, APIs, files, and streaming platforms, and to automate Machine Learning workflow.
  • Utilize knowledge of BI tools like Looker and Snowflake to automate reporting of critical metrics and to build self-served analytical dashboards.
  • Utilize knowledge of Natural Language Processing for text mining and sentiment analysis to summarize and extract key insights from qualitative data sources, such as surveys, twitter tweets, and news.
  • Utilize knowledge of Machine Learning and Deep Learning algorithms, such as LSTMs and Neural Networks, to detect intricate patterns within experimental data, providing researchers with data-driven insights to aid in hypothesis testing and experiment design.
  • Utilize knowledge of MS Excel 's powerful data analysis features, such as pivot tables, charts, and formulas, to analyze and visualize large datasets.
  • From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work.
  • Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/
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