Sameeksha Capital

https://sameeksha.capital/

Founded :

2016

Type :

Services

Size :

20-100

Stage :

Bootstrapped

About

Sameeksha Capital is a SEBI registered PMS, founded by Bhavin Shah, who carries with him a top notch reputation for integrity and excellence. Since April 2016, we have been running a Long Only India Equity Fund under PMS structure which correlates the most with mid and small cap Indices and we have been able to deliver very good absolute, relative as well as risk adjusted performance. We believe in investing based on thorough research. We have invested in resources (one of the largest research teams in the industry) and developed proprietary systems and processes that we follow rigorously to achieve consistency in our decision making. Our client list includes some Prominent Individuals each having net worth in excess of one billion US dollars.

Connect with the team

Bhavin Shah

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Company social profiles

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Jobs at Sameeksha Capital

Alternative Data Programmer for Equity Fund

at Sameeksha Capital

1 recruiter

Posted by Bhavin Shah

The recruiter has not been active on this job recently. You may apply but please expect a delayed response.

Ahmedabad

1 - 2 yrs

₹1L - ₹3L / yr

Java

Python

Data Structures

Algorithms

C++

+1 more

Looking for Alternative Data Programmer for equity fund
The programmer should be proficient in python and should be able to work totally independently. Should also have skill to work with databases and have strong capability to understand how to fetch data from various sources, organise the data and identify useful information through efficient code.
Familiarity with Python
Some examples of work:

Text search on earnings transcripts for keywords to identify future trends.

Integration of internal and external financial database

Web scraping to capture clean and organize data

Automatic updating of our financial models by importing data from machine readable formats such as XBRL

Fetching data from public databases such as RBI, NSE, BSE, DGCA and process the same.

Back-testing of data either to test historical cause and effect relation on market performance/portfolio performance, as well as back testing of our screener criteria in devising strategy

Text search on earnings transcripts for keywords to identify future trends.

Integration of internal and external financial database

Web scraping to capture clean and organize data

Automatic updating of our financial models by importing data from machine readable formats such as XBRL

Fetching data from public databases such as RBI, NSE, BSE, DGCA and process the same.

Back-testing of data either to test historical cause and effect relation on market performance/portfolio performance, as well as back testing of our screener criteria in devising strategy

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