Alphanumeriq.ai

We are looking for a Quant Analyst Intern for our Bangalore office. This role will be responsible for aspects of our trading infrastructure that support our trading operations and feed our research.

You will collaborate with experienced colleagues to build new technology. Your work will integrate the best new network and compute technologies with our internally developed hardware and software to operate our industry leading trading system architecture.

A Quant Analyst Intern might work on projects in areas such as: market access, monitoring and compliance, algo/strategy evaluation and management, performance tuning, and trading automation. You will be working on a tight knit, highly productive team. You'll be charged with designing new systems that impact the whole company, debugging mission critical software in high pressure fast paced environments, This group churns through large amounts of code daily. As a Trading Algorithm Developer, you'll be expected to establish a deep knowledge of Python, SQL, Excel, Power BI, machine learning (deep learning in particular), Quantitative Finance , and algorithm design.

Responsibilities:

• Perform quantitative analysis on large datasets to identify trends, patterns, and insights.

• Utilize statistical techniques and modeling to extract meaningful information from data

• Assist in the development and validation of quantitative models for various purposes such as risk assessment, pricing, and forecasting

• Collaborate with senior analysts and researchers to refine and improve existing models

• Prepare reports and presentations summarizing analysis findings and insights

• Conduct testing and validation of models to ensure accuracy, reliability, and compliance with regulatory standards

• Excellent problem-solving skills with the ability to approach complex problems in a logical and systematic manner

• Ability to effectively communicate technical concepts to both technical and non technical audiences

• Communicate results to team members and stakeholders in a clear and concise manner

• Strong attention to detail and accuracy in analysis and documentation • Ability to identify and correct errors in data and analysis results

• Ability to work effectively in a team environment, collaborating with colleagues from diverse backgrounds and disciplines

Requirements:

• 0-6 month experience working with Python in a professional production environment

• Knowledge of Analytics tools - SQL , Excel , Power BI

• In depth knowledge of Python Libraries - Pandas , Numpy, Plotly etc

• Familiarity with IDE like Jupyter Notebook and VS Code

• Highly collaborative in nature, with excellent written and verbal communication skills

• Familiarity of AWS, Linux, Devops is strongly preferred, but not required

• Familiarity with the trading domain and finance is strongly preferred, but not required

• Proven ability to communicate with less technical users to understand requirements and design and implement appropriate solutions

• Bachelor’s degree in Computer Science, Data Science, Math or equivalent

• High level of ownership and accountability, reliability, and strong follow

We are seeking a highly analytical and detail-oriented Quantitative Data Analyst to join our team. In this role, you will be responsible for analysing large datasets consisting of backtested time series data for various trading instruments and strategy portfolios. Your insights and findings will play a crucial role in informing our investment decisions and strategy development.

Responsibilities:

1. Data Analysis and Modeling:

a. Analyse extensive backtested time series data for a wide range of financial instruments and trading strategies

b. Develop and implement quantitative models to identify patterns, trends, and anomalies within the data

c. Conduct statistical analysis, including hypothesis testing, regression analysis, and time series forecasting

d. Validate and interpret the results of quantitative models, ensuring accuracy and reliability

2. Performance Evaluation:

a. Evaluate the performance of various trading strategies and portfolios using industry-standard metrics (e.g., Sharpe ratio, drawdowns, risk-adjusted returns)

b. Conduct attribution analysis to identify the key drivers of performance and risk factors

c. Investigate the behaviour of strategies under different market conditions and stress scenarios

3. Data Visualization and Reporting:

a. Create insightful visualisations and dashboards to effectively communicate complex data analysis results to management and investment teams

b. Prepare clear and concise reports summarising key findings, insights, and recommendations based on the data analysis

c. Collaborate with portfolio managers, researchers, and other stakeholders to understand their analytical needs and tailor analyses accordingly

4. Continuous Improvement:

a. Stay up-to-date with the latest developments in quantitative finance, data analysis techniques, and industry best practices

b. Identify opportunities for process optimization and workflow improvements to enhance efficiency and accuracy

c. Participate in the development and refinement of in-house analytical tools and libraries.

Qualifications:

1. Education: Bachelor's or Master's degree in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, or a related discipline.

2. Experience: Minimum of 2-5 years of experience in quantitative data analysis, preferably within the financial or investment domain.

3. Technical Skills:

a. Strong proficiency in programming languages such as Python, R, or MATLAB

b. Expertise in data manipulation, statistical modelling, and time series analysis using libraries like pandas, NumPy, SciPy, and scikit-learn

c. Experience with data visualisation tools (e.g., Matplotlib, Plotly, Bokeh, Tableau)

d. Familiarity with SQL and database management systems e. Knowledge of financial instruments, trading strategies, and portfolio construction principles is a plus.

4. Analytical and Problem-Solving Skills: Exceptional analytical and quantitative reasoning abilities, with a talent for identifying patterns and extracting meaningful insights from complex datasets.

5. Communication Skills: Ability to effectively communicate technical concepts and analysis results to both technical and non-technical audiences.

6. Attention to Detail: Meticulous approach to data analysis, with a keen eye for accuracy and precision.