LogiNext is looking for a technically savvy and passionate Principle Engineer - Data Science to analyze large amounts of raw information to find patterns that will help improve our company. We will rely on you to build data products to extract valuable business insights.
In this role, you should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data. We also want to see a passion for machine-learning and research.
Your goal will be to help our company analyze trends to make better decisions. Without knowledge of how the software works, data scientists might have difficulty in work. Apart from experience in developing R and Python, they must know modern approaches to software development and their impact. DevOps continuous integration and deployment, experience in cloud computing are everyday skills to manage and process data.
Responsibilities :
Adapting and enhancing machine learning techniques based on physical intuition about the domain Design sampling methodology, prepare data, including data cleaning, univariate analysis, missing value imputation, , identify appropriate analytic and statistical methodology, develop predictive models and document process and results Lead projects both as a principal investigator and project manager, responsible for meeting project requirements on schedule and on budget Coordinate and lead efforts to innovate by deriving insights from heterogeneous sets of data generated by our suite of Aerospace products Support and mentor data scientists Maintain and work with our data pipeline that transfers and processes several terabytes of data using Spark, Scala, Python, Apache Kafka, Pig/Hive & Impala Work directly with application teams/partners (internal clients such as Xbox, Skype, Office) to understand their offerings/domain and help them become successful with data so they can run controlled experiments (a/b testing) Understand the data generated by experiments, and producing actionable, trustworthy conclusions from them Apply data analysis, data mining and data processing to present data clearly and develop experiments (ab testing) Work with development team to build tools for data logging and repeatable data tasks tol accelerate and automate data scientist duties
Requirements:
Bachelor’s or Master’s degree in Computer Science, Math, Physics, Engineering, Statistics or other technical field. PhD preferred 8 to 10 years of experience in data mining, data modeling, and reporting 5+ years of experience working with large data sets or do large scale quantitative analysis Expert SQL scripting required Development experience in one of the following: Scala, Java, Python, Perl, PHP, C++ or C# Experience working with Hadoop, Pig/Hive, Spark, MapReduce Ability to drive projects Basic understanding of statistics – hypothesis testing, p-values, confidence intervals, regression, classification, and optimization are core lingo Analysis - Should be able to perform Exploratory Data Analysis and get actionable insights from the data, with impressive visualization. Modeling - Should be familiar with ML concepts and algorithms; understanding of the internals and pros/cons of models is required. Strong algorithmic problem-solving skills Experience manipulating large data sets through statistical software (ex. R, SAS) or other methods Superior verbal, visual and written communication skills to educate and work with cross functional teams on controlled experiments Experimentation design or A/B testing experience is preferred. Experience in leading a team required.
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