Uses predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from structure and unstructured data. Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy. Assists business with casual inferences & observations with finding patterns, relationships in data. Must possess strong understanding of internal business segment stakeholders and possess strong written and communication skills. Typically requires expertise in relational database structures, research methods, machine learning, Cloud based technologies, Big Data technologies i.e. Hadoop , HBase, Lucene/Solr, analytics packages i.e. R, Mahout, Matlab, Octave, Weka, scripting languages i.e. Python, Perl, programming languages i.e. Java, C/C++, SQL. Typically possesses advanced degree in Computer Science, Mathematics, Machine Learning, Operation Research, and Statistics or equivalent expertise.
Data Scientist will play a role in helping understand and optimize business performance across McAfee consumer and Mobile business segments. Through Data mining, predictive modeling, customer segmentation and forecasting, the data scientist will focus on supporting multiple teams and must be committed to answering questions that help us build the best products and develop best practices in marketing, user experience and communication. The Data Scientist will develop high-quality models to gain deeper insights into how people interact with the digital world and specifically McAfee products.
Key Responsibilities: Support the optimization of sales and marketing efforts via data mining, modeling, user segmentation and forecasting. Work closely with business and engineering teams to encourage statistical best practices with respect to experimental design, data capture and data analysis. Develop and demonstrate improved analysis methodologies and educate stakeholders throughout the company. Act independently to identify and evangelize opportunities for improved analysis and efficiency through better data and analytics practices.
Required Experience/Skills & Education: Bachelor's Degree and/or a relevant technical field, or 4+ years of experience in a relevant role. Comfort manipulating and analyzing complex, high-volume, high-dimensionality data from varying data sources. Ability to communicate complex quantitative analysis and analytic approaches in a clear, precise, and actionable manner. Familiarity with relational databases and SQL-like query languages. Expert knowledge of a scientific computing language such as R, Python, or Julia. Experience working with data-distributed query tools a plus Hadoop, Hive, etc. Excellent analytical skills preferably from experience including data manipulation and statistical analysis. Strong problem solving and analytical skills with the desire to apply those skills in analyzing complex business problems. Proven ability to work effectively in a fast-paced, cross functional, and sometimes highly pressured Ability to thrive under tight deadlines and high-pressure situations.