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Business Analyst

Company Name Confidential

Keywords / Skills : Analytics, SAS, R, Statistical Analysis, quantitative analytics, Statistical Techniques, Data Visualization, SQL

5 - 10 years
Posted: 2018-04-21

Job Description
Skills
5-10 years of experience in analytics domain

Good knowledge of Statistical techniques and their application

Demonstrated experience in coming up solutions to loosely defined business problems by leveraging structured and unstructured data sets

Proficiency in statistical analysis, quantitative analytics,forecasting/predictive analytics, multivariate testing, and optimization algorithms. 
Experience in Programming skills SAS or R
Excellent communication and interpersonal skills 

Education
Masters degree in Mathematics/Statistics
OR B.E/B.Tech /M.E/M.Tech
MBA from a reputed institute

Accountabilities, responsibilities
Work closely with relevant stakeholders to identify opportunities and define problem statements that could be solved through analytics while gaining an understanding of their operations and operating context

Sourcing data (structured and unstructured) from various internal and external systems, cleansing and preparing for statistical analysis

Leverages on new data collection processes and techniques for e.g geo-location and social media

Develops statistical models and uses various statistical tools to generate insight leading to decisions.

Summarises and presents the findings/analysis/insights in a manner that is easy to understand by larger business community.

Understand complex business scenarios and communicate the users story from data to variety of stakeholders

Makes recommendations on data collection , integration and retention requirements aligning with business requirements and best practices

Develops experimental design approaches, prototypes and create proof of concepts for the business to evaluate

Develops innovative and effective approaches to solve analytics problems and communicates results and methodologies.

Identifies and analyses patterns in the volume of data supporting the initiative, the type of data (e.g images, text, clickstream or metering data) and the speed or sudden variations in data collection.

Recommends ongoing improvements to methods and algorithms that lead to findings, including new information.

Enable reporting and MI teams and educate them on approaches like testing hypotheses and statistical validation of results.






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