Job Description

Job Title: Data ScientistJob Location: GurgaonEducational QualificationB.E / B.Tech with Minimum 60 % marksBSC Mathematics/ Data scienceExperience: 4-7 YearsResponsibilities:\xe2\x88\x92 Design data-driven solutions to address business challenges.\xe2\x88\x92 Acquire specialized knowledge in the automotive domain relevant to the problem at hand, seeking expertise from domain specialists as needed.\xe2\x88\x92 Gain proficiency in the vehicle\xe2\x80\x99s IoT device, specifically the Telematics Control Unit.\xe2\x88\x92 Develop a comprehensive understanding of Time-Series Data.\xe2\x88\x92 Clean, prepare, and manage datasets for modelling, engaging in the ETL process when necessary.\xe2\x88\x92 Conduct data exploration to extract insights, present findings to domain experts, identify patterns, seasonality, trends, and causality, and collaborate with domain experts to formulate and test hypotheses.\xe2\x88\x92 Devise and refine features, evaluate their significance, and determine the machine learning strategy.\xe2\x88\x92 Engage in data modelling, select suitable machine learning or deep learning algorithms, establish data pipelines for training, perform hyper-parameter optimization, and conduct validation and testing. Implement ensemble techniques if beneficial.\xe2\x88\x92 Interpret and visualize data through reports and graphical plots.\xe2\x88\x92 Provide guidance and mentorship to junior data science professionals.Technical Skills / ExperienceEssential Qualifications:\xc2\xb7 A minimum of 4 years of industry experience in data science.\xc2\xb7 Proficiency in Python programming with experience in pandas, NumPy, matplotlib, and sklearn libraries.\xc2\xb7 Competence in statistical analysis, including descriptive, inferential statistics, and hypothesis testing.\xc2\xb7 Practical experience in mathematical modelling and a variety of machine learning techniques, such as:o Generalized Linear Models (GLM), Boosting Algorithms, Decision Trees, Neural Networks, Support Vector Machines (SVM), and Bayesian Methods.o Econometric analysis.o Deep Learning models including Recurrent Neural Networks (RNNs), Long Short-Term Memory networks (LSTM), and Gated Recurrent Units (GRUs).o Unsupervised learning algorithms and image classification using computer vision.\xc2\xb7 Proven track record of successful model deployment.Desirable Qualifications:\xc2\xb7 Experience with accident simulation tools such as PC crash or OPENPass.\xc2\xb7 Familiarity with time-series and IoT data analytics.\xc2\xb7 Familiarity with LLMs\xc2\xb7 Knowledge of automotive systems, vehicle fundamentals, and Controller Area Network (CAN) protocol

Maruti Suzuki