Data Scientist - Systematic Equities

Selby Jennings; New York (NY); On-site; USD 150,000 - 250,000; Full time

Job summary

A leading financial recruitment firm is looking for a Data Scientist specializing in Systematic Equities. This role involves leveraging advanced analytics to support strategic decisions, requiring proficiency in Python, R, and statistical analysis. Join a dynamic team aimed at innovating through data insights and analytics.

Benefits

Annual Bonus

Sign-on bonus

Qualifications

• At least 3 years working in high-velocity sectors like finance or similar industries.
• Proficient in Python and R with core libraries like Pandas, scikit-learn, and TensorFlow.
• Deep knowledge of statistical techniques and their real-world applications.

Responsibilities

• Investigate complex datasets to extract trends and key relationships.
• Design and deploy machine learning algorithms to enhance operational efficiency.
• Translate analytical results into actionable recommendations.

Skills

Python

R

Statistical techniques

Data visualization

SQL

Job description

Data Scientist - Systematic Equities - NYC

Data Scientist - Systematic Equities - NYC

This range is provided by Selby Jennings. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

$150,000.00/yr - $250,000.00/yr

Additional compensation types

Annual Bonus and Sign-on bonus

Direct message the job poster from Selby Jennings

FinTech Headhunter | Prop Trading and Hedge Funds

Role Overview

Join our data science team to drive innovation and insights through advanced analytics, experimentation, and strategic communication. You'll help shape data-driven decisions in a dynamic environment.

Key Responsibilities

• Data Insight Development: Investigate complex datasets to extract trends and key relationships, utilizing visual tools to communicate findings effectively.
• Model Construction & Optimization: Design and deploy machine learning algorithms to forecast business metrics and enhance operational efficiency.
• Experimental Design: Construct and manage experiments to validate predictive models and inform business strategies.
• Insight Communication: Translate analytical results into actionable recommendations for cross-functional stakeholders.

Minimum Qualifications

• Professional Experience: At least 3 years working in high-velocity sectors like finance or similar industries.
• Coding Expertise: Proficient in Python and R; experienced with core libraries such as Pandas, scikit-learn, and TensorFlow.
• Visualization Skills: Adept at building data dashboards and visual narratives using platforms like Tableau.
• Statistical Fluency: Deep knowledge of statistical techniques and their real-world applications.
• Database Mastery: Skilled in writing and optimizing complex SQL queries for data extraction and transformation.

Preferred Qualifications

• Cloud Familiarity: Exposure to environments like Google Cloud Platform (GCP).
• Big Data Acumen: Experience with distributed computing tools such as Apache Spark and Kafka.
• Pipeline Design: Understanding of data ingestion frameworks and ETL best practices.

Seniority level

• Seniority level

  Not Applicable

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering, Finance, and Information Technology

• Industries

  Capital Markets and Financial Services

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