Data Scientist @ Autodesk

Autodesk is seeking a Data Scientist to join our Advanced Analytics organization. The Advanced Analytics organization is chartered with building innovative data products and analytics solutions for Autodesks strategy, product, marketing, sales and customer support teams. This critical data scientist role will help us make machine intelligence an integral part of how Autodesk makes decisions and designs and builds its products.

You will work alongside a product development team and apply data mining, analytics and machine learning methods to understanding how customers use, adopt and achieve successful outcomes with our products. The ideal candidate is a strong data scientist who thinks outside the box, is naturally curious, highly collaborative, and has a passion for tackling complex data-centric problems.

Responsibilities

• Work on a variety of problems that seek to better understand how customers use their products and what drives deeper adoption of products
• Apply your quantitative analysis, data mining and machine learning expertise to building models that make sense of user needs, usage patterns, factors that drive deeper adoption and contribute to subscriber churn
• Influence product development, strategy and roadmap prioritization
• Design and implement machine learning pipelines that improve Autodesks evidence-based decision-making capabilities
• Tackle complex problems requiring a creative mindset to find innovative and elegant solutions

Minimum Qualifications

• BS/MS in the field of Mathematics, Statistics/Analytics, Computer Science or other relevant field
• 2+ years of applicable work experience
• Experience working with relational SQL and NoSQL databases
• Experience working with big data platforms (Hadoop, Spark, Hive)
• Fluency with one or more of the scripting languages: Python, Java, Scala, etc.
• Good understanding of CS fundamentals, e.g. algorithms and data structures
• Experience in statistical programming tools such as R, Matlab, SAS, etc.
• Experience with data science toolkits: pandas, numpy, scikit-learn, TensorFlow, etc.
• Familiarity with statistics concepts and analysis, e.g. hypothesis testing, regression, etc.
• Familiarity with Machine Learning techniques, e.g. classification, clustering, regularization, optimization, dimension reduction, etc.
• Good communication skills and ability to explain complex topics to a non-technical audience