Data Science



Reference code -

7 months ago

Education/ Experience and Skill Requirement

    4-6 years of relevant experience in:

    Essential skills

    • Experience working in quantitative modelling development projects.

    • Experience in building ETL processes, data pipelines using standard Python Anaconda libraries.

    • Strong proficiency with programming in Python. Python PEP8 coding best practices is required. Proficient with Python list comprehensions and optimization.

    • Strong OOP (Object Oriented Programming) concepts, and strong experience of good modular design in Python.

    • Strong pre-processing, machine learning, statistical inferential analytics, exploratory data analysis experience.

    • Strong data integration experience. Experience with building data controls.

    • Experience in working with acquiring Financial data sources (Factset, Bloomberg, Reuters, Dealogic) is desired

    • Strong communicator (verbally and written). Independently manage daily client communication, especially over calls

      Additionally, desired skills

    • R programming (Modelling, data pre-processing)

    • NLP processing, entity pattern matching experience


    As part of the Data Science practice, you will be involved with projects which generate data-driven predictions and insights by designing, implementing and testing data science based solutions. Key responsibilities include:

    • Design and develop quantitative solutions for the data science group of one of the largest investment banks

    • Have a strong understanding of the domain knowledge

    • Collaborate with the subject matter domain experts, data engineers and data scientists to ensure data quality, accuracy and completeness.

    • Collaborate with data engineers to build data pipelines and ETL frameworks using standard Python Anaconda libraries.

    • Collaborate with data scientists and subject matter domain experts to perform EDA, engineer features and build quantitative models.

    • Be able to perform data analysis using Jupyter Notebook and Microsoft Excel.

    • Be proactive and independent and be able to deliver projects with minimum inputs from client stakeholders.

    • Evaluate and ensure quality of deliverables within project timelines.

    • Ensure effective, efficient and continuous communication (written and verbally) with global stakeholders.

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Step 1

Resumes sourced from multiple sources will be evaluated vis-à-vis the required skill sets

Step 2

The HR will contact the shortlisted applicants for the interview process

Step 3

There will 2-3 rounds of interviews (Telephonic/Face to Face/Skype, etc.)

Step 4

The candidate who clears all the rounds will be shortlisted for the final offer

Step 5

HR to then get in touch with the candidate for salary discussion/Date of Joining etc