Data Scientist- Manager

Job Summary

The Data Scientist at the manager level will leverage data analytics tools to extract value from large datasets and support Jindal Group's business unit heads in data-driven decision-making. The role involves using data mining techniques, statistical analysis, and machine learning to create predictive and prescriptive models. The Data Scientist will also assist Jindal Group's data and analytics team in implementing analytics tools and techniques, and contribute to the development of the organization's data strategy.

Key Responsibilities

1. Utilize data analytics tools for data mining and extract information from large data sets.

2. Perform exploratory data analysis to identify patterns, trends, and anomalies.

3. Perform ad-hoc analysis and create predictive and prescriptive models.

4. Evaluate model performance using appropriate metrics and techniques, and iterate on model improvements.

5. Collaborate with business units to identify issues and propose data-driven solutions.

6. Develop algorithms and procedures, and prepare reports for business units.

7. Create report templates and final reports for business units.

8. Conduct research on new data analytics tools and statistical techniques, identifying opportunities for their application across Jindal Group

9. Develop algorithms, data analytics tool prototypes, and proof of concepts.

10. Assist enterprise architects in defining the data strategy and provide inputs to the data governance board as required.

Minimum Qualifications

Bachelor's degree in engineering, computer science, information system or equivalent experience

Professional Certifications (preferable):

e.g. Microsoft Certified: Azure AI Fundamentals, Tableau Desktop Specialist, Synapse, microsoft ADF, ADLS

Experience

  a.     Minimum 5-8 years of experience in data modeling and analytics.

b.     Minimum 5-8 years experience working with information technology in Steel Manufacturing/ Power Generation/ Mining industry

Abilities

a. Strong proficiency in programming languages such as Python or R.

b. Knowledge of machine learning algorithms and frameworks, and practical experience in model development and evaluation.

c. Familiarity with database systems and SQL for data extraction and manipulation

d. Excellent problem-solving skills and a proactive approach to tackling challenges.

e. Strong communication skills to liaise with technical and non-technical stakeholders