Data Scientist

1 week ago

Dindigul, India LST Capital Full time

About Us:

We are a premier quantitative research firm dedicated to advancing financial strategies through rigorous mathematical research and innovative analytics. Our mission is to explore complex global markets by leveraging deep expertise in mathematics, statistics, and technology. We foster an intellectually stimulating and collaborative environment, encouraging the pursuit of novel ideas and pushing the boundaries of quantitative research.

If you are passionate about mathematics, thrive on solving challenging problems, and are driven by a relentless curiosity, we invite you to join our team.

Responsibilities:

  • Lead advanced mathematical research to analyze and interpret complex datasets, uncover actionable insights, and identify innovative solutions in financial markets.
  • Develop and refine predictive models, statistical algorithms, and machine learning frameworks to understand trends and patterns in high-dimensional data.
  • Conduct rigorous testing, validation, and optimization of models to ensure robustness, accuracy, and applicability to real-world scenarios.
  • Collaborate with cross-disciplinary teams of researchers, data scientists, and technologists to integrate cutting-edge methodologies into financial strategies.
  • Investigate and explore new research areas, staying at the forefront of advancements in quantitative research, applied mathematics, and machine learning.
  • Present detailed findings, methodologies, and insights to stakeholders in a clear and compelling manner.

Qualifications:

  • Current PhD student or PhD holder in Mathematics, Statistics, Physics, Computer Science, Engineering, Quantitative Finance, or a closely related quantitative discipline.
  • A strong appetite for research, with a proven ability to approach complex problems with analytical rigor and creativity.
  • Deep expertise in mathematical modeling, probability theory, optimization, and machine learning.
  • Proficiency in Python or R, with experience in libraries and tools such as TensorFlow, PyTorch, Scikit-learn, Pandas, and NumPy.
  • Familiarity with data manipulation, SQL, and experience with big data technologies (e.g., Spark, Hadoop) is a plus.
  • Knowledge of cloud platforms such as AWS, Azure, or GCP, and experience deploying machine learning models in production environments.
  • Exceptional problem-solving skills and a passion for addressing intellectually challenging problems.
  • Strong communication skills with the ability to articulate complex research findings to diverse audiences.


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