Data Scientist MGR Maruti Suzuki India Ltd

5.0 - 9.0 years

0 Lacs

haryana

On-site

You should have the ability to design and implement workflows of Linear and Logistic Regression, Ensemble Models (Random Forest, Boosting) using R/Python. Demonstrating competency in Probability and Statistics, you should be capable of utilizing ideas of Data Distributions, Hypothesis Testing, and other Statistical Tests. Your experience should include dealing with outliers, denoising data, and handling the impact of pandemic like situations. Performing Exploratory Data Analysis (EDA) of raw data and feature engineering wherever applicable is crucial. You should possess demonstrable competency in Data Visualization using the Python/R Data Science Stack. Leveraging cloud platforms for training and deploying large-scale solutions is essential. Being able to train and evaluate ML models using various machine learning and deep learning algorithms is a must. You should also be skilled in retraining and maintaining model accuracy in deployment. Knowledge of cloud platforms such as AWS, Azure, and GCP is required. Exposure to NoSQL databases (MongoDB, Cassandra, Cosmos DB, HBase) is preferred. An understanding of forecasting experience in products like SAP, Oracle, Power BI, and Qlik is beneficial. Proficiency in Excel (Power Pivot, Power Query, Macros, Charts) is expected. Having experience with large datasets and distributed computing (Hive/Hadoop/Spark) is advantageous. Knowledge of transfer learning using state-of-the-art models in different spaces like vision, NLP, and speech is a plus. Integration with external services and Cloud API is also a part of the role. Working with data annotation approaches and tools for text, images, and videos is desirable. You should be able to package and deploy large-scale models on on-premise systems using multiple approaches, including Docker. Taking complete ownership of the assigned project is necessary. Experience of working in Agile environments and being well-versed with JIRA or equivalent project tracking tools is expected.,

Posted 2 days ago

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Data Scientist RHI Magnesita

4.0 - 8.0 years

14 - 17 Lacs

Gurugram

Hybrid

Position level: AI Specialist/Software engineering professional (Cant be a junior/fresher, needs to be middle to senior level person) Work Experience: Ideally, 4 to 5 years of working as a Data Scientist / Machine Learning and AI at a managerial position (end-to-end project responsibility). Slightly lower work experience can be considered based on the skill level of the candidate. About the job: Use AI-ML to work with data to predict process behaviors. Stay abreast of industry trends, emerging technologies, and best practices in data science, and provide recommendations for adopting innovative approaches within the product teams. In addition, championing a data-driven culture, promoting best practices, knowledge sharing, and collaborative problem-solving. Abilities: Knowledge about data analysis, Artificial Intelligence (AI), Machine Learning (ML), and preparation of test reports to show results of tests. Strong in communication with a collaborative attitude, not afraid to take responsibility and make decisions, open to new learning, and adapt. Experience with end-to-end process and used to make result presentation to customers. Technical Requirements: Experience working with real world messy data (time series, sensors, etc.) Familiarity with Machine learning and statistical modelling Ability to interpret model results in business context Knowledge of Data preprocessing (feature engineering, outlier handling, etc.) Soft Skill Requirements: Analytical thinking Ability to connect results to business or process understanding Communication skills Comfortable explaining complex topics to stakeholders Structured problem solving – Able to define and execute a structured way to reach results Autonomous working style – can drive a small project or parts of a project Tool Knowledge: Programming: Python (Common core libraries: pandas, numpy, scikit-learn, matplotlib, mlfow etc.); Knowledge of best practices (PEP8, code structure, testing, etc.) Code versioning (GIT) Data Handling: SQL; Understanding of data format (CSV, JSON, Parquet); Familiarity with time series data handling Infrastructure: Basic Cloud technology knowledge (Azure (preferred), AWS, GCP); Basic Knowledge of MLOps workflow Good to have: Knowledge of Azure ML, AWS SageMaker; Knowledge of MLOps best practices in any tool; Containerization and deployment (Docker, Kubernetes) Languages: English – Proficient/Fluent Location: Hybrid (WFO+WFH) + Availability to visit customer sites for meetings and work-related responsibilities as per the project requirement.

Posted 5 days ago

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