Relevant Experience: 10 Years to 15 Years

Primary Skills : Information technology

Education : B.Tech/B.E., M.S/M.D, M.Sc, M.Tech

Branches : Any Specialization, Electrical, Electronics, Industrial Engineering, Information Technology, Instrumentation, Mechanical, Metallurgy, Production, Production/Industrial, Science, Statistics

Experience : 10.00 To 15.00 Years

Requirements : Minimum Qualifications: B Tech/ BE, M.Sc.(Maths/Statistics/Operation Research) or M Tech/ MS or equivalent in Electrical/ Electronics/ Computer Science /Instrumentation /Mechanical/Metallurgical/ /Industrial Engineering/ Maths/Statistics/Operation Research

- Deep understanding of complex technical and business dynamics with a strong ability to identify, manages and mitigates risk with understanding of the implications of new technologies and experience of leading highly complex work activities.

- Authority and accountability for a significant area of work, including technical, financial and quality aspects with capability to absorb complex information and ability to communicate across multifunction operating zones at all levels.

- Experience and Leadership across organisation practices, setting goals and deliverables for complex projects and ability to mentor and coach teams with multiple technology and operation competencies. Experience in designing complicated, multi-staged data-driven solutions to real-world.

The following expertise will be an added advantage

- Functional knowledge of characterizing business problem of Supply Chain/ Market & Customer/Steel manufacturing/ /Mining/Mineral processing

- Application knowledge of Python/AIMMS

- Application knowledge of Optimisation and Simulation

- Project management experience of Solution Platforms

- Design thinking experience

Technical Competencies:

Organisational understanding and detailed knowledge of a range of data sets across variety of domains to create insights impacting strategy, decision making and service delivery

Operational knowledge of key statistical concepts and methods essential to finding structure through concepts of explanatory / response variables in data through descriptive and inferential statistical concepts and introduction to practical analytics through examples precautions and pitfalls with understanding of conditional distributions, regression functions, time series and ability to see a problem in terms of parameters (i.e., in terms of statistical models) is required with application knowledge of Data Science and ML algorithms based on state-of-art ML/DL/RL techniques across multifunctional operation domains. Operational knowledge of SQL and Non SQL, Database architecture, Python programming and Optimisation techniques .

The following operation knowledge will be an added advantage

Data visualisation tools

GCP (Google Cloud Platform)

Oracle DB

AIIMS Optimisation Tool

Any Logic Simulation Tool

Industry

Human Resources

Employment Type

Full-time

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