Job Description: Purpose: - Lead the execution of analytics projects within the portfolio - Design and articulate the data science solution relevant to the business problem/opportunity - Lead the identification of appropriate data science models and evaluate their fitment for the available data - Articulate the insights from the models in business-friendly language and explain the workings of the model for business adoption - Provide support to the business value manager in managing the portfolio Modeling and Technology Skills: - Deep expertise in machine learning techniques (supervised and unsupervised) statistics/mathematics/operations research including (but not limited to). - Advanced Machine learning techniques : Decision Trees, Neural Networks, Deep Learning, Support Vector Machines, Clustering, Bayesian Networks, Reinforcement Learning, Feature Reduction/engineering, Anomaly deduction, Natural Language Processing (incl. Theme deduction, sentiment analysis, Topic Modeling), Natural Language Generation and/or. - Statistics / Mathematics : Data Quality Analysis, Data identification, Hypothesis testing, Univariate / Multivariate Analysis, Cluster Analysis, Classification/PCA, Factor Analysis, Linear Modeling, Logit/Probit Model, Affinity &amp; Association, Time Series, DoE, distribution/probability theory and/or. - Operations Research: Sensitivity Analysis - Shadow price, Allowable decrease or increase, Transportation problem &amp; variants, Allocation Problem &amp; variants, Selection problem, Multi-criteria decision-making, models, DEA, Employee Scheduling, Knapsack problem, Supply Chain Problem &amp; variants, Location Selection, Network designing - VRP, TSP, Heuristics Modeling and/or. - Risk: Simulation design and high-performance computing, GARCH modeling, Macro-economic / Market behavior modeling and/or. Strong experience in specialized analytics tools and technologies (including, but not limited to): - SAS, Python, R, SPSS (preferably 2 out of 4) - Spotfire, Tableau, Qlickview - For Operations Research (AIMS, Cplex, Matlab) - Awareness of Data Bricks, Apache Spark, Hadoop - Awareness of Agile / Scrum ways of working - Identify the right modeling approach(es) for the given scenario and articulate why the approach fits - Assess data availability and modeling feasibility - Review interpretation of models results - Evaluate model fit and based on business/function scenario &nbsp;Proficiency Level: Mastery

Bangalore

Chennai

Gurgaon/Gurugram

Hyderabad

Kolkata

Mumbai

Pune

Data Scientist - Manufacturing/Auto/Infra/Oil & Gas Sector 

Data Scientist - Manufacturing/Auto/Infra/Oil & Gas Sector  ,Job Description for Data Scientist - Manufacturing/Auto/Infra/Oil & Gas Sector  in Randstad in  Bangalore Chennai Gurgaon/Gurugram Hyderabad Kolkata Mumbai Pune for (8-16) years of experience. Apply Now!

Job Description for Data Scientist - Manufacturing/Auto/Infra/Oil & Gas Sector  in Randstad in  Bangalore Chennai Gurgaon/Gurugram Hyderabad Kolkata Mumbai Pune for (8-16) years of experience. Apply Now!