Data Scientist - Systematic Trading

Selby Jennings; Florida; On-site; USD 175,000 - 250,000; Full time

Job summary

Join a leading company as a Data Scientist, where you'll leverage advanced analytics to drive innovation in the finance sector. Collaborate with cross-functional teams to translate data insights into actionable strategies. Your expertise in Python, R, and statistical techniques will be key in shaping data-driven decisions. This role offers a competitive salary range and opportunities for professional growth in a dynamic environment.

Qualifications

• At least 3 years in high-velocity sectors like finance.
• Proficient in Python and R, experienced with core libraries.

Responsibilities

• Investigate complex datasets to extract trends and key relationships.
• Design and deploy machine learning algorithms to forecast business metrics.

Skills

Python

R

Statistical Techniques

Data Visualization

SQL

Tools

Pandas

scikit-learn

TensorFlow

Tableau

Apache Spark

Kafka

Job description

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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

$175,000.00/yr - $250,000.00/yr

Additional compensation types

Annual Bonus and Sign-on bonus

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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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