Data Scientist

Educational Qualification: Essential: B.E. / B.Tech/ M. Tech./M.Sc. in any stream Desirable: Specialization in data science or statistics Role : Data Scientist Responsibilities: Data Solutions Architecture: Develop innovative data-driven solutions for business challenges using Telematics 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. Utilize tools like Google Maps API for visualization. Technical Skills / Experience: Essential : Industry Experience: Minimum of 5 years in a data scientist role. 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. Knowledge of clustering techniques. 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. Desirable : Databricks Platform: Experience with Databricks for big data processing and machine learning. Distributed Computing: Experience with Spark or other distributed computing frameworks. AutoML Tools: Understanding of tools like AWS Sagemaker, Google AutoML, IBM AutoAI, and Databricks. Telematics Data Analytics: Experience in time-series/IoT data analytics, including data streaming from vehicle on-board IoT devices. Automotive Systems Knowledge: Exposure to automotive systems, basics of automobiles, and Controller Area Network (CAN) protocol. Remote Collaboration: Experience working with remote team members. Advanced Visualization Tools: Experience with data visualization tools such as Tableau and PowerBI. Google Maps API: Working experience with Google Maps API for creating heat maps Behavioral: Analytical Thinking: Strong analytical skills to interpret complex data and derive actionable insights. Problem-Solving: Ability to approach problems creatively and develop innovative solutions. Attention to Detail: Meticulous attention to detail to ensure data accuracy and model reliability. Communication: Excellent communication skills to convey technical information to non-technical stakeholders. Collaboration: Strong team player with the ability to work collaboratively in a cross-functional environment. Adaptability: Flexibility to adapt to changing business needs and evolving technologies. Curiosity: A proactive learner with a curiosity to explore new technologies and methodologies. Time Management: Effective time management skills to handle multiple projects and meet deadlines