Description

Job Role:

Perform ad hoc statistical, data mining, and machine learning analysis on complex business problems related to Billing call volumes, customer experience and call deflection. Create innovative algorithms behind a variety of services ranging from Call prediction and Segmentations. Collaborate and work closely with various Businesses, IT and Marketing teams

Develop and Design advance predictive and prescriptive analysis models using R or SAS

Work with IT to integrate new technologies into workflows (ex: Hadoop)

Projects/Focus:

Enhancing Customer Engagement

Enhancing Customer Experience

Improving Customer Sentiment

Solving for Call Volume

Reducing Business Costs

Research data to improve customer engagement. Finding and fixing customer pain points.

Research data to predict the probability of customer actions & looking at certain sentiment as well as behavior aspects of customers.

Work with large sets of data.

Expectations:

Have proven analytical skills,

Have the drive to innovate and drive actionable results.

Have a passion for problem solving and a continued curious nature around data

Have the ability to prioritize, focus on ideas and features that will have significant impact and value

Have the ability to quantify and measure impacts of solutions

Understand, categorize, organize, and interpret heterogeneous data sets.

Design experiments, test hypotheses, and work with prototypes and models.

Be involved in the transition from prototyping to production.

Have the ability to collaborate with architects, engineers, and QA teams.

Ability to communicate results and progress internally and externally in meetings, presentations and technical talks,

Having knowledge in Telecom or Billing Domain is a Plus

Qualifications

Bachelors degree or equivalent work experience

Min 2 years management or equivalent knowledge experience

Advanced degree in a quantitative discipline (like, mathematics, statistics, economics, operations research, computer science, physics, etc.) is a plus

Experience in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing (A/B testing), and optimization algorithms.

Ability to comprehend and analyze business needs and translate into technical requirements.

Experience working with large datasets using tools like SQL, Hadoop, MapReduce, Pig/Hive, Spark/Shark

Experience in using statistical modeling and distributed machine learning algorithms on large data sets

Experience in the use of statistical packages like R, Matlab, SciPy or Weka

Knowledge in Distributed Processing Framework for large data sets analysis and working knowledge in map-reduce architectures (HDFS)

Experience in Object Oriented Programming and familiarity with functional programming concepts (C++, Java, Scala, etc)

Experience with SQL, Unix/Linux, and a scripting language such as Python, Perl or Ruby.Expertise with shell scripting and automation