Emerging Data Strategist (USA)

Stamford, Connecticut, United States

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We are a global leader in quantitative statistical arbitrage, specializing in developing cutting-edge machine learning models and data-driven strategies to identify and exploit market inefficiencies. We leverage a wide array of data sources, including technical, fundamental, and alternative data sets, to inform our models and trading algorithms. 

We are assembling a cutting-edge Data Exploration Team to be at the forefront of uncovering groundbreaking datasets, discovering innovative data providers, and staying ahead of the curve with the latest data advancements. As part of our Data Exploration Team, you will help drive the evolution of our data-driven strategies, empowering the firm’s research, trading, and risk management teams to thrive in an increasingly competitive landscape.

Your passion and expertise in emerging datasets, data architecture, management, and analytics will be instrumental in shaping the future of our firm’s data-driven decision-making. Working closely with the Director of Data Research, data scientists, quantitative researchers, and engineering teams, you will ensure that our data procurement not only supports but propels the firm's strategic goals. As a member of this forward-thinking team, you will actively seek out and acquire novel datasets, engage with data providers, assess and prioritize data integration, and ensure that our data library is as rich and diverse as the opportunities it uncovers. 

Responsibilities

  • Proactively scout and identify emerging datasets, alternative data sources, and innovative data providers across various industries to fuel the firm's quantitative strategies.
  • Engage with a wide range of data providers, from traditional market data vendors to niche and non-traditional data sources (e.g., satellite imagery, web scraping, sentiment analysis), evaluating their potential to enhance the firm’s research and trading strategies.
  • Collaborate closely with data scientists to communicate the value and limitations of sourced data, ensuring it could provide a competitive edge in the market and aligns with model needs and strategic goals.
  • Lead the negotiation and acquisition process for new data sources, ensuring favorable terms, including pricing, licensing, and delivery mechanisms.
  • Maintain relationships with key data vendors and providers, fostering partnerships that ensure ongoing access to high-quality and cost-effective data sources.
  • Coordinate the initial integration of new data sources into the firm’s research infrastructure, working with data engineers and scientists to ensure smooth onboarding and data readiness for deeper analysis.
  • Continuously monitor the data landscape for emerging trends, new data sources, and technological advancements that could impact the firm’s competitive positioning.
  • Participate in industry conferences, webinars, and other events to stay informed about the latest developments in data acquisition and alternative data trends.

Requirements

  • Bachelor’s or Master’s degree in Data Science, Computer Science, Engineering, Quantitative Finance, Mathematics, or related field (PhD is a plus).
  • 3+ years of experience in data strategy, engineering, or science, preferably within quantitative finance.
  • Proven expertise in the utility and management of large datasets (technical, fundamental, and alternative data) and processing requirements for integrating them into machine learning and statistical models.
  • Proficiency in machine learning, statistical analysis, Python, R, SQL, and other data manipulation tools.
  • Experience with alternative data sources (e.g., sentiment analysis, satellite imagery, geospatial data) and data visualization tools (e.g., Tableau, Power BI).
  • Familiarity with financial market data feeds, real-time data processing, and data architecture.

Benefits

  • Competitive salary, plus bonus based on individual and company performance.
  • Collaborative, casual, and friendly work environment while solving the hardest problems in the financial markets.
  • PPO Health, dental and vision insurance premiums fully covered for you and your dependents.
  • Pre-Tax Commuter Benefits – making your commute smoother.
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Architecture Computer Science Data strategy Data visualization Engineering Finance Machine Learning Mathematics ML models PhD Power BI Python R Research SQL Statistics Tableau Trading Strategies

Perks/benefits: Career development Competitive pay Conferences Health care Team events

Region: North America
Country: United States

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