Principal Data Scientist

With the current footprint in construction projects and recent acquisitions, Autodesk is well equipped to revolutionize construction industry. The team is responsible for ensuring that company has an accurate and practical understanding of our cloud platform usage health and ensuring we can understand our customers better and make data driven decisions as an organization and improve product, business, adoption, and sales operation by applying data science. We work in close sync with our executive staff due to our direct impact on Autodesk Construction Solution business. 

Responsibilities

To help Autodesk Construction Solutions (ASC) toward its goal of being a leading construction technology provider and brand, this position will focus on using data to create data products to help business partners make data driven decisions. You will be a key member of the analytics Data Science team. In this role, 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. Lead junior/ senior data scientists and analysts. Apply statistical techniques to model customer behavior and trends to identify potential opportunities for growth and improvement. Building statistical models (both predictive and descriptive) for customer lifetime value modeling, retention modeling etc. 

• 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

Minimum Qualifications

• BS/MS/PhD in the fields of: Mathematics, Physical Sciences, Statistics/Analytics, Computer Science, or other relevant fields

• Proficient in Python

• Experience working with relational SQL and/or NoSQL databases

• Experience working with big data platforms (Hadoop, Spark, Hive)

• Experience in statistical programming tools such as R, Matlab, SAS, Python data science toolkits, etc.

• Experience with data science toolkits like pandas, Jupyter, scikit, TensorFlow, etc.

• Familiarity with Statistics concepts and analysis, e.g. hypothesis testing, regression, experimental design, etc.

• Familiarity with Machine Learning techniques, e.g. classification, clustering, regularization, optimization, dimension reduction, etc.

• Experience implementing reporting programs like Domo, Looker, Tableau, PowerBI, etc.

• Experience in data visualization tools

• Experience in customer analytics

• Good communication skills and ability to explain complex topics to both technical and non-technical audience as well

The Ideal Candidate

• A curious individual who believes that data is the best tool to understand what is happening

• An eager learner who will continually seek to expand their skills to new tools, techniques, and systems

• A strong communicator who can understand complex patterns and simplify them down

• A self-starter who finds new ways to solve problems

• You have experience owning complex projects from start to finish. You define a data science roadmap and execute against it in collaboration with others

• You are passionate about insights, not just data. You’re a strategic thinker and are able to synthesize methodology and data into actionable business and/or product strategy from your analyses

About Autodesk Construction Solutions
Autodesk has fully reimagined the construction business for the digital age, enabling companies to address the most important challenges they face today while preparing for new ways of working in the future. The Autodesk Construction Solutions (ACS) portfolio connects the office, trailer and field so customers can move seamlessly through each phase of a building's lifecycle - from design and pre-construction to construction, turnover and operations - with best-in-class solutions that include Assemble Systems, BIM 360, BuildingConnected and PlanGrid. General contractors, subcontractors, and owners around the world rely on ACS to win more work, enhance collaboration, speed decision-making, reduce risk, and improve overall project outcomes.