Machine Learning / Data Scientist

Proprius - San Francisco, CA

Full-time

San Francisco, CA

Real Estate

About the position

Our client is looking for a machine learning engineer to join our existing ML team in developing and refining a predictive application. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. You must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms, and creating/running simulations. You must have a proven ability to drive business results with your data-based insights. You must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Responsibilities

• Work with stakeholders throughout the organization to identify opportunities for leveraging data to drive business solutions.
• Mine and analyze data from databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques.
• Develop custom data models and algorithms to apply to datasets.
• Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
• Coordinate with different functional teams to implement models and monitor outcomes.
• Develop processes and tools to monitor and analyze model performance and data accuracy.

Requirements

• Strong with Statistics and can code in either R, Python, Java, and Scala.
• Experience with designing and building using micro-services architectural pattern, web APIs using dotnet core & C#.
• Experience and passion for simulations, optimization, neural networks, artificial intelligence (deep learning and machine learning).
• Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, GIT, SQL, etc.
• Able to understand statistical solutions and execute similar activities.
• Experience in data wrangling and advanced analytic modeling.
• Strong communication and organizational skills and has the ability to deal with ambiguity while juggling multiple priorities and projects at the same time.
• Experience visualizing/presenting data for stakeholders using: Seaborn, Business Objects, D3, ggplot, etc.
• Ability to investigate the feasibility and data requirements necessary to develop an ML solution for a given problem.
• Ability to design, build and test production-ready ML-based products while interpreting and explaining the basis for predictions generated by ML models.

Nice-to-haves

• Knowledge and experience using one or more of the following, or similar, machine learning software frameworks: CAFFE, Torch 7, Keras, and Tensorflow.
• Experience building production-ready NLP or information retrieval systems.
• Hands-on experience with NLP tools, libraries, and corpora (e.g. NLTK, Stanford CoreNLP, Wikipedia corpus, etc.)