Atlas Oil Company

Quantitative Analyst

Greater Houston

full_time

About This Job

Atlas Oil is recruiting a Quantitative Analyst to help build and deploy ML and statistical insights to traders, generate data-driven trading theses, and communicate results to management. The role is highly visible, working with traders and trading teams, and will report to the Head of Quantitative Analytics.

The role will be on-site in Atlas Oil’s Houston, TX office.

About Atlas Oil

Headquartered in Houston, TX, Atlas Oil is the inaugural Simon Group Holdings company. Since our founding in 1985, Atlas has grown through technological and operational innovation, all while maintaining our unwavering commitment to customer success. Atlas offers single-source solutions for fuel, transportation and logistics and is one of the largest fuel distributors in the country, delivering over 1 billion gallons of fuel annually across North America.

Atlas Oil’s Strategy and Analytics team builds for-purpose and bespoke trading models, risk models, and insight capabilities. In conjunction with traders, the team builds capabilities that enable data-driven decision making and risk management. The team works with traders in Natural Gas, NGLs, Refined Products, and Ethanol.

High Level Requirements

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Existing knowledge base in energy market trading, with demonstrable strength in one or more of: natural gas, NGLs, refined products, and ethanol markets

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Strong capabilities in financial engineering, ML and Statistical modeling, as applied to commodity trading

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Capable across full analytics development process flow, from data sourcing, wrangling, model development and testing, to visualization – ideally with an ability to create production grade products

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Ability to work independently in a fast-paced environment

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Strong communication skills, both written and spoken

Technical Requirements

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Strong Python coding skills required. Other languages will be a lower priority for this team; coding hygiene and an ability to learn best practices are a must

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Knowledge of data sources, data wrangling, and effective API usage (e.g., Bloomberg API) strongly preferred

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Ability to cover the entire model development lifecycle – from model testing (e.g., test/train splits, model assumption evaluation), development, deployment and maintenance

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Knowledge of real option valuation models, volatility models, predictive analytics (ML, Statistical), time series models, and stochastics are a plus

Your Day To Day Will Involve

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Work on building new analytics, leveraging traditional statistical methods and ML methods to a clearly defined business use cases

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Maintain and run subset of existing analytics inventory – ensuring the source data hasn’t changed model assumptions, and evaluating the output for accuracy and relevance

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Talk with traders on implications of model outputs, and implement model updates as necessary

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Document findings and model outputs for consumption by traders and leadership

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