Senior Data Scientist

About this role

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Skills you'll use

What you'll do

• ▪ Data Solutions Architecture: Develop innovative data-driven solutions for business challenges using Telematics/Time series data.
• Collaborate with domain experts to gain automotive insights.
• ▪IoT Device Mastery: Understand the Telematics Control Unit (TCU) and the time-series data it generates.
• ▪ Data Landscape Analysis: Evaluate data adequacy and establish a comprehensive understanding of the data landscape.
• ▪ Data Preparation: Clean and prepare datasets for modeling. Engage in ETL processes and apply data transformation techniques such as resampling, filtering, and encoding. ▪ Exploratory Data Analysis: Conduct exploratory data analysis to derive insights. Present descriptive statistics and insights to domain experts. Identify meaningful patterns, detect seasonality and trends, and establish cause-and-effect relationships.
• ▪ Feature Engineering: Design and select features, study feature importance, and decide on the machine learning strategy.
• ▪ Model Development: Select appropriate machine learning/deep learning models, set up data pipelines for model training, perform hyper-parameter tuning, validation, and testing. Apply ensemble modeling techniques if required.
• ▪ Reporting & Visualization: Create comprehensive reports and visualize data using plots and heat maps.

Who can apply

• ▪ Machine Learning Expertise: Experience with machine learning algorithms (e.g., Generalized Linear Models, Boosting, Decision Trees, Neural Networks, SVM, Bayesian Methods, time series models).
• ▪ Hands-on Experience: Proficiency in using machine learning models for regression, classification, and unsupervised learning algorithms.
• ▪ Cloud Computing: Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
• ▪ Programming Skills: Strong programming skills in Python, with experience using libraries like pandas, numpy, matplotlib, and sklearn.
• ▪ Data Visualization: Proficiency in data visualization techniques and tools.
• ▪ MLOps: Exposure to MLOps and model deployment in production environments.
• ▪ SQL skills: Experience working with relational and non-relational databases.

About Maruti Suzuki

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