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Data Scientist

6.00 to 9.00 Years   Bangalore   22 Mar, 2019
Job LocationBangalore
EducationNot Mentioned
SalaryNot Disclosed
IndustryIT - Software
Functional Areaeneral / Other Software
EmploymentTypeFull-time

Job Description

Job Responsibilities

  • Proven track record in data analytics either in a commercial or research setting.
  • Expert balance of statistical knowledge, machine learning and coding skills.
  • Good communication and data storytelling skills.
  • Willingness to learn, ability to think skeptically about problems and results, curious to explore new techniques and domains.
  • Not afraid of working with high volume and/or untidy data.
  • Expert knowledge of R and/or Python essential and the ability to learn new techniques is key.
  • Know-how in Hadoop ecosystem is key.
  • Ability to work independently in a quickly evolving environment.
Skills
  • Analytics / mathematics (understanding the math behind) Modelling (mathematics)
  • Statistics (test hypotheses, data distribution, etc)
  • Clustering (kmeans, hierarchical, etc)
  • Classification (logistic regression, svm, decision tree, random forest, neural network)
  • Regression (linear regression, decision tree, random forest, neural network)
  • Classical optimisation (gradient descent, newton rapshon, etc)
  • Graph theory (network analytics)
  • Heuristic optimisation (genetic algorithm, swarm theory)
  • Deep leaning (lstm, convolutional nn, recurrent nn)
  • Agent based modelling
  • Vizualisation Qlick view, Tableau,
  • Matplotlib, seaborn, etc
  • ggplot
  • Excel, thinkcell
  • D3js
  • Languages Python (pandas, scikit, sklearn)
  • Scala
  • Spark (sql, ml, graphX, streaming)
  • SQL/PostgreSQL
  • R
  • Tools/IDE Notebooks (jupyter notebook, zeppeling, databricks)
  • Neo4j
  • Tableau
  • Hive/Impala/Hbase
  • OCR (tesseract)
  • Data management Extracting data (web scraping)
  • Data cleaning (imputation, missing values detection)
  • Data exploration (corelation, outliers detection, trends, etc)
  • Text mining (TFID, n-grams, lemming, stemming, NLP)
  • Image processing
  • Data loading (jdbc connection, connection to database, FTP connection)
  • Table profiler automation
  • Table comparer automation
  • Engineering Code packaging
  • ETL
  • Environment configuration (versioning, packages installation)
  • Tools Hadoop
  • Yarn
  • Spark
  • Oozie
  • Hive/Impala/Hbase
,

Keyskills :
tools web molecular biology

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