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Data Scientist at ETAIOTA Systems (Bhubaneswar, India)

Key Responsibilities:
Apply Data Mining/ Data Analysis methods using a variety of data tools, building and implementing models using algorithms and creating / running simulations to drive optimization and improvement across business functions.
Assess accuracy of new data sources and data gathering techniques.
Perform Exploratory Data Analysis, detailed analysis of business problems and technical environments in designing the solution.
Apply Supervised, Unsupervised and Reinforcement Learning Algorithms.
Apply advanced Machine Learning Algorithms and Statistics: Regression, Simulation, Scenario Analysis, Time Series Modelling, Classification (Logistic Regression, Decision Trees, SVM, KNN, Naive Bayes, Clustering, K-Means, Apriopri), Ensemble Models (Random Forest, Boosting, Bagging and Neural Networks).
Lead and manage Proof of Concepts and demonstrate the outcomes quickly.
Document use cases, solutions and recommendations.
Work analytically in a problem-solving environment.
Work in a fast-paced agile development environment.
Coordinate with different functional teams to implement models and monitor outcomes.
Work with stakeholders throughout the organization to identify opportunities for leveraging organisation data and apply Predictive Modelling techniques to gain insights across business functions Operations, Products, Sales, Marketing, HR and Finance teams.
Help program and project managers in the design, planning and governance of implementing Data Science solutions.

Experience and Skills:
2+ years of professional working experience in Analytics.
Experience in Retail, Financial Services and Manufacturing.
Experience using statistical packages of R, Python and Spark ML to work with data and draw insights from large data sets.
Experience with distributed data/ computing tools: Hadoop, Hive, Spark, Python.
Experience with SQL.
Experience visualizing/ presenting data for stakeholders using matplotlib, ggplot or Excel or Tableau.
Excellent written and verbal communication skills for coordinating across teams.

Education qualification:
Bachelors/ Masters in a Quantitative Discipline (Statistics, Econometrics, Mathematics, Engineering and Science)
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