Quant/Data Scientist

at GitHub

Quant/Data Scientist

GitHub

Company

Home

Quant/Data Scientist

at GitHub

Posted by Nataliia Mediana

3 - 15 yrs

$50K - $80K / yr (ESOP available)

Remote only

Skills

Data Science

Data Scientist

Data engineering

Financial analysis

Finance

Quantitative analyst

Quantitative research

Python

Machine Learning (ML)

Artificial Intelligence (AI)

PySpark

Lambda

EKS

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

Atleast 3 years of relevant ML experience
Graduation date : 2018 and earlier
3-5 years of experience in high level Python programming.
Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques.
Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling.
Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
A valid Github profile with some activity in it

Bonus to have:

Experience in storing and retrieving data from large and complex time series databases
Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation.
Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.)
Knowledge of REST APIs and data extracting and cleaning techniques
Good to have experience in Pyspark or any other big data programming/parallel computing
Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
Any progress towards CFA or FRM is a bonus
Average tenure of atleast 1.5 years in a company

You would join, and, if qualified, lead a growing team of data scientists and researchers, and be responsible for a complete lifecycle of quantitative strategy implementation and trading.

Requirements:

Atleast 3 years of relevant ML experience
Graduation date : 2018 and earlier
3-5 years of experience in high level Python programming.
Master Degree (or Phd) in quantitative disciplines such as Statistics, Mathematics, Physics, Computer Science in top universities.
Good knowledge of applied and theoretical statistics, linear algebra and machine learning techniques.
Ability to leverage financial and statistical insights to research, explore and harness a large collection of quantitative strategies and financial datasets in order to build strong predictive models.
Should take ownership for the research, design, development and implementation of the strategy development and effectively communicate with other team mates
Prior experience and good knowledge of lifecycle and pitfalls of algorithmic strategy development and modelling.
Good practical knowledge in understanding financial statements, value investing, portfolio and risk management techniques.
A proven ability to lead and drive innovation to solve challenges and road blocks in project completion.
A valid Github profile with some activity in it

Bonus to have:

Experience in storing and retrieving data from large and complex time series databases
Very good practical knowledge on time-series modelling and forecasting (ARIMA, ARCH and Stochastic modelling)
Prior experience in optimizing and back testing quantitative strategies, doing return and risk attribution, feature/factor evaluation.
Knowledge of AWS/Cloud ecosystem is an added plus (EC2s, Lambda, EKS, Sagemaker etc.)
Knowledge of REST APIs and data extracting and cleaning techniques
Good to have experience in Pyspark or any other big data programming/parallel computing
Familiarity with derivatives, knowledge in multiple asset classes along with Equities.
Any progress towards CFA or FRM is a bonus
Average tenure of atleast 1.5 years in a company

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About GitHub

Founded :

2008

Type :

Products & Services

Size :

20-100

Stage :

Raised funding

About

We are a nascent quantitative hedge fund led by an MIT PhD and Math Olympiad medallist, offering opportunities to grow with us as we build out the team. Our fund has world class investors and big data experts as part of the GP, top-notch ML experts as advisers to the fund, plus has equity funding to grow the team, license data and scale the data processing.

We are interested in researching and taking in live a variety of quantitative strategies based on historic and live market data, alternative datasets, social media data (both audio and video) and stock fundamental data.

Nataliia Mediana

Timothy Chklovski

Manas Ranjan Kar

Rohan Deshmukh

Company social profiles

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