Data Scientist
Found in: Whatjobs IN C2 - 3 weeks ago
Data Scientist responsibilities include working with the data science team, planning projects and building analytics models. You should have a strong problem-solving ability and a knack for statistical analysis. If you’re also able to align our data products with our business goals, we’d like to meet you. Your ultimate goal will be to help improve our products and business decisions by making the most out of our data.
Key Responsibilities
Responsible for overseeing the data scientists team and data specialistsTeach, lead, and counsel colleagues on new techniques or solutionsCollaborate with data and software engineers to enable deployment of sciences and technologies that will scale across the company’s ecosystemResponsible for the conception, planning, and prioritizing of data projectsResponsible for building analytic systems and predictive models as well as experimenting with new models and techniquesEnsure that data projects align with organizational goals
Minimum Qualification
Master's degree in Computer Science, Operations Research, Econometrics, Statistics or related technical field5+ years of experience solving analytical problems using quantitative approachesExperience communicating quantitative analysis resultsKnowledge with relational databases and SQLDevelopment experience in any scripting language (PHP, Python, Perl, etc.)Knowledge of statistics (e.g., hypothesis testing, regressions)Experience manipulating data sets through statistical software (ex. R, SAS) or other methods
Technical Skills -
Must have –Programming – Python (Preferred) / RML Models – i. Regression – Linear, Logistic, Multinomial, Mixed effectClassification – Bagging & Boosting (Random Forest), Decision tree, SVMClustering – K-Means, hierarchical, DB-ScanTime series – ARIMA, SARIMA, ARIMAX, Holt-Winters, Multi TS (VAR), UCMNeural Networks (Deep learning), Naive BayesExcel and SQLDimensionality Reduction – PCA, SVD etc.Optimization Techniques – Linear programming, Gradient Descent, Genetic AlgorithmCloud – Understanding of Azure / AWS offerings, Setting up ML pipeline of cloud
Good to have –Visualization – Tableau / Power BI / Looker / QlikViewData management – HDFS, Spark, Advanced ExcelAgile Tools – Azure DevOps, JIRAPysparkBig Data/Hive DatabaseIDE: Pycharm
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