Project Research Scientist

St Johns Research Institute (SJRI)

3 - 8 years

5 - 10 Lacs

bengaluru

Posted:-1 days ago| Platform:

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Skills Required

computer science c++ simulation nutrition analytical research scientist ii machine learning business strategy python logistics

Work Mode

Work from Office

Job Type

Full Time

Job Description

Roles and Responsibilities:

Develop and Implement Predictive Models:
Design and deploy advanced mathematical and machine learning models to analyze complex systems, predict future behavior, and drive optimization. You will implement these models efficiently in Python using libraries such as NumPy, SciPy, Pandas, and Scikit-learn.
Algorithm Design and Implementation:
Conceptualize, build, and validate novel algorithms to solve core business challenges. This involves translating mathematical concepts into scalable, robust Python code for simulation, data processing, and predictive analytics.
Quantitative Analysis for Strategic Prediction:
Conduct rigorous quantitative analysis on large datasets to uncover hidden patterns and build predictive frameworks. Your primary responsibility is to translate these complex findings into clear, actionable insights that directly inform business strategy.
Lead Research in Predictive Methods:
Stay at the forefront of applied mathematics and predictive modeling. Research, evaluate, and introduce innovative algorithms and analytical techniques to the team, ensuring we maintain a competitive edge.
Provide Technical Leadership and Mentorship:
Act as a subject matter expert on modeling and algorithms, mentoring data scientists and engineers on advanced methodologies. You will collaborate with cross-functional teams to ensure mathematical rigor and guide the technical direction of predictive projects.

Qualifications

Required Qualifications:
Educational Background:
A PhD or Masters degree in Applied Mathematics, Statistics, Physics, Computer Science, or a related quantitative field.
Mathematical Expertise:
Deep knowledge in areas like optimization, differential equations, linear algebra, and probability theory.
Programming Proficiency:
Strong, hands-on programming skills in Python and its scientific computing stack (NumPy, SciPy, Pandas, Scikit-learn).
Modeling Experience:
Proven track record of designing, building, and implementing mathematical or predictive models to solve real-world problems.

Preferred Qualifications

Experience with deep learning frameworks (e.g., PyTorch, TensorFlow).
Familiarity with software engineering best practices (e.g., version control with Git, unit testing).
Proficiency in a high-performance computing language like C++ or CUDA.
Experience applying models in a specific industry domain (e.g., finance, logistics, engineering)

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