Title: Senior Data Scientist
Company: Ademco, Inc.
Ademco, Inc. is seeking a Senior Data Scientist for our Austin, TX location. Responsible for using appropriate machine learning techniques on a wide variety of large, complex datasets. Communicate insights in a clear, simple and precise manner to various levels of people within and outside of the organization. Deliver actionable, data science-informed contributions to internal and external projects. Identify opportunities where data science techniques can be applied to solve business problems. Validate the analytical models to ensure that the model achieves expected performance in terms of accuracy or other relevant metrics. Take ownership of the end to end system from Problem statement to Solution Delivery with high quality, scalable models and solutions. Guide team members and contribute in building an exceptional team of Data scientists. Design, develop, and implement data management systems of analytic frameworks for the business’s data.
Bachelor’s degree or foreign equivalent in Computer Engineering, Computer Science, Mathematics, Statistics, Machine Learning, or related quantitative field and 5 years of related technical experience in position offered or acceptable alternate occupation. Full term of experience (5 years) must include each of the following: implementing data pipelines and creating architectural stack using bigdata technologies, including HDFS, MapReduce, Hive, Flume and Oozie; experience in NoSQL data modeling such as HBase. Must possess 2 years of experience with each of the following: working on strategy or full-life cycle big data engineering; writing Spark jobs to read/transform/write from different sources (Kafka, RabbitMQ) and destinations (NoSql, DataLake); hands-on experience working within data science capacity with big data (Hadoop, Spark); and experience in a technical lead position. Must possess 1 year of experience with each of the following: advanced statistical capabilities and statistical models, including: consumer predictive value, churn, segmentation and profiling, association models; Extracting existing trends and unnoticed insights using Data Mining techniques like Anomaly detection, data transformations, missing values treatments, and dimension reduction techniques; natural language processing; working with machine learning libraries (OpenCV, Scikit-Learn); using SAS, Python and R for Data Curation; and with Visualization on using Tableau, Matplotlib, plotly, ggplot2, and D3.js. Up to 20% international and domestic travel.