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AVP/SM Data Scientist For Goods & Service Tax Network, Delhi

8.00 to 13.00 Years   Delhi   10 Oct, 2020
National Institute for Smart Government
Job LocationDelhi
EducationNot Mentioned
SalaryNot Disclosed
IndustryNGO / Social Work
Functional AreaGeneral / Other Software
EmploymentTypeFull-time

Job Description

AVP/SM Data Scientist Reporting to:Head, Business Intelligence and Fraud AnalyticsFunction:TechnicalRole:Data ScientistExperience:8+ YearsLocation:DelhiRole Description We are looking for a hands on Data scientists to handle challenging problems in the areas of Indirect Tax Fraud & Analysis using cutting edge data science techniques. You have engineering skills to work with structured and unstructured data. You have applied knowledge in statistics, machine learning and NLP systems. You will be a machine learning expert who will co-create our implementation playbook of our machine learning / deep learning / NLP / AI capabilities. You have sound experience on machine learning, excellent communication skills and constantly keep pace with industry trends and new technologies. You have a passion for conceptualization, prototyping, debugging & developing ML-based products, applications & solutions. Key Responsibilities

  • Leads discovery processes with stakeholders to identify the business requirements and the expected outcome.
  • Collaborates with subject matter experts to select the relevant sources of information.
  • Design and build analytic solution for our customers in short development cycles.
  • Designs experiments, test hypotheses, and build models. Conducts advanced data analysis and designs custom algorithms.
  • Creates visualizations, dashboards and reports to explain insights to the stakeholders.
  • Presents and depicts the rationale of their findings in easy to understand terms for the business.
  • Demonstrated data science experience with both structured and unstructured data.
  • Knowledge of statistical techniques (ANOVA, Chi squared, Correlation etc) to design, test and validate hypothesis.
  • Experience working with classical machine learning models: Bayesian models, Tree based models, Margin based classifiers, Boosting and Bagging models, Cluster analysis, and Anomaly detection systems.
  • Expert in feature engineering and evaluation
  • Hands on experience in handling text data using NLP techniques (e.g. document classification and clustering, topic mining, linguistic analysis, entity recognition, semantic search, information retrieval).
  • Knowledge of classical time series analysis techniques e.g. Holt-Winters, ARIMA.
  • Some Data visualization experience ( Tableau, Qlikview, D3.js etc)
  • Experience working with new generation ML algorithms (eg: SVM; LDA; Kernel Based Models; Decision Trees; GBM; NN; Rule mining; Pattern Discovery etc)
  • Some experience with Deep Learning models and their applications for CV; NLP and time series forecasting
  • Experience and interest with privacy preserving techniques, hyperparameter optimization, model tuning and optimization
  • Experience in designing end to end ML workflow and developing the modeling code to agreed engineering specs
  • Knowledge distributed data science techniques, methods and tools
  • Knowledge of model testing and post production drift, bias and shift detection
  • Ability to write efficient, concise and maintainable code
Others Learn new technologies & tool and suggest better ways of improving data science operationsDesign, Discuss with Senior Management & Own your personal & professional development planCreate, Discuss & work through a training plan in the area of your interest which aligns with current & future responsibilitiesKey InterfacesExternal: Internal: External stakeholders (tax authorities, taxpayers, treasuries, banks, policy makers, process groups, etc.) Internal departments i.e. Technology, Strategy, MIS & Analysis, Services team and CISOKey Attributes & Skills:Basic Qualifications:Experience of 8+ years as a Data Scientist. Graduate with any STEM fieldCore Skills:Analytics software/programming technologies: Python, SparkML, Tensorflow, Big DL, Horovod, H20, Rapidminer, R, CPLEX, LIONDatabase technologies: MySQL,MongoDB, Hadoop ecosystem, couchdb, redis, neo4jETL technologies: Python, SparkLanguages: Python, Pyspark, Scala, Java Script, UNIX Shell; DjangoData Visualization: Bokeh, Dash, Seaborn, Tableau, D3.jsStatistical Methods: Probability distribution, ANOVA, Factor Analysis, Correlation & Regression, Conjoint, Time series, DoE, Sampling, PCA, Statistical Inference, MCMCMachine Learning Methods/Algorithms: CHAID, Bayesian models, Linear & logistic Regression, SVM, RVM, Neural Nets, K-means, Expectation maximization, DBSCAN, BIRCH, Ensemble models, ICA, LDA, Graph models, Anomaly Detection models, xgboost, LSA, Lasso, Ridge, Elasticnet, Constraint & Multi-objective programmingCognitive & NLP: CoreNLP, NLTK, CNTK ; GENSIMl SpacyDeep Learning: Tensorflow; H2O; Pytorch; Horovod; Caffe; Big DLSpecific Packages: Scikit-learn; Pandas; numpy, PySpark, matplotlib, bokeh, seaburn, R-shiny, ggplot2, Alchemy, Dask, Big DL, Horovod, Distributed MLBig Data Tools: Spark, Hadoop, Hive, HBASE, Hue, Drill, PrestoAdditional Skills (Good to have)Working knowledge of Spark & Hadoop ecosystemExperience of Financial Crime modellingExperience in K8 based ML workflow tooling ,

Keyskills :
time series analysispost productiontime seriescluster analysisdata analysisdata visualizationanomaly detectionpythonanalyticsdata sciencedecision treesfactor analysiscommercial modelssenior managementmachine learningsqlsubject matter exper

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