Job Description :
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Required Skills:
Minimum 10 years of experience, Experience in Banking is preferred
Proven working experience as a data scientist
Good applied statistics skills, such as distributions, statistical testing, regression, etc
Knowledge of statistics and experience using statistical packages for analyzing datasets (Excel, SPSS, SAS , R, Python , etc)
Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
Solid knowledge of statistical techniques.
Excellent understanding of machine learning techniques and algorithms
The ability to come up with solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets.
Technical expertise regarding data models, database design development, data mining and segmentation techniques
Experience with common data science toolkits, such as R
Experience with data visualization tools, such as tableau
Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
Adept at queries, report writing and presenting findings
Strong knowledge of and experience with reporting packages (Business Objects etc), databases (SQL etc), programming (XML, Javascript, or ETL frameworks)
Graduation Degree in Mathematics, Economics, Computer Science, Information Management or Statistics
Experience using Hadoop technologies (Basic must have skills)
Expert in SQL and othe programming languages
experience in HDFS, Hive, Impala, Map Reduce, Pig, Yarn ,oozie
Programming language experience
Python
R
Scala
Desired Skills
Development experience using
Kafka, Storm, Spark, Flume, Hbase
Job Description:
Designs experiments, test hypotheses, and build models.
Conducts advanced data analysis and complex designs algorithm.
Interpret data, analyze results using statistical techniques and provide ongoing reports
Works with Institute stakeholders to identify the business requirements and the expected outcome.
• Works with and alongside business analysts by suggesting other products of interest to the client.
Models and frames business scenarios that are meaningful and which impact on critical business processes and/or decisions.
Selecting features, building and optimizing classifiers using machine learning techniques
Data mining using state-of-the-art methods
Develop and implement databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality
Acquire data from primary or secondary data sources and maintain databases/data systems
Identifies what data is available and relevant, including internal and external data sources, leveraging new data collection processes such as smart meters Identify, analyze, and interpret trends or patterns in complex data sets and geo-location information or social media.
Filter and “clean” data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems
Work with management to prioritize business and information needs"