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Remote Data Science Trading Jobs in Spring, TX (NOW HIRING)

Vitol

Software Engineer in Data Science

Houston, TX · On-site +1

$109K - $131K/yr

Company Description Vitol is the world's largest independent energy and commodities trading company ... Translate: Act as a local champion for data science and AI, helping users adopt tools and ...

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Lead Modeling Scientist Location : Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is responsible for building and scaling the data and computational backbone ...

Arva Intelligence

Data Engineer

Houston, TX · On-site +1

$95K - $130K/yr

Lead Modeling Scientist Location : Remote Base Salary Range: $95k - $130k General Position Description The Data Engineer is responsible for building and scaling the data and computational backbone ...

Insolation Technology Ltd

Data Analyst

Houston, TX · On-site +1

$21 - $26/hr

Bachelors degree in Data Science, Statistics, Mathematics, Engineering, or a related field ... Flexible work schedule and remote work options Job Type: * Full time Pay: * $21.00 - $26.00 per ...

MD Anderson

Principal Data Engineer

Houston, TX · Remote

Remote 100% within Texas only Why Us. UT MD Anderson offers the opportunity to lead transformative ... Master's Degree Business Analytics, Computer Science, Information Technology, Data Science, or ...

Arva Intelligence

Modeling Scientist

Houston, TX · On-site +1

$100K - $160K/yr

Remote Base Salary Range : $100k - $160k base salary The Modeling Scientist is responsible for ... Partner with data engineers to implement reproducible, scalable modeling pipelines * Contribute to ...

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Remote Data Science Trading information

What are the key skills and qualifications needed to thrive as a remote data science trading professional?

To thrive as a Remote Data Science Trading professional, you need a strong background in statistics, quantitative analysis, programming (typically Python or R), and a relevant degree such as mathematics, finance, or computer science. Familiarity with trading platforms, machine learning libraries, data visualization tools, and sometimes certifications like CFA or FRM are highly valued. Excellent problem-solving, communication, and self-management skills are crucial for analyzing market data and collaborating remotely. These abilities ensure effective trading strategies, accurate data-driven decisions, and seamless teamwork in a fast-paced, distributed environment.

How do remote data science trading professionals typically collaborate with trading teams and stakeholders?

Remote data science trading professionals often work closely with traders, quantitative analysts, and software engineers through virtual meetings, collaborative platforms, and shared code repositories. Daily responsibilities may include analyzing market data, developing predictive models, and communicating actionable insights to inform trading strategies. Effective communication and clear documentation are crucial to ensure alignment across the team, given the remote structure. Many organizations use project management tools and regular check-ins to maintain transparency and foster collaboration between remote data scientists and other trading stakeholders.

What is a remote data science trading professional?

A Remote Data Science Trading job involves using data analysis, statistical modeling, and machine learning techniques to inform and improve trading strategies, all while working from a remote location. Professionals in this role analyze large datasets, build predictive models, and help optimize financial trades for institutions or trading firms. The remote aspect means all tasks are performed online, allowing for flexible work arrangements and collaboration with teams across the globe. This position typically requires strong programming, analytical, and financial knowledge.
What job categories do people searching Remote Data Science Trading jobs in Spring, TX look for? The top searched job categories for Remote Data Science Trading jobs in Spring, TX are:
What cities near Spring, TX are hiring for Remote Data Science Trading jobs? Cities near Spring, TX with the most Remote Data Science Trading job openings:
Remote Data Science Trading jobs near you
Infographic showing various Remote Data Science Trading job openings in Spring, TX as of July 2026, with employment types broken down into 1% As Needed, 83% Full Time, 12% Part Time, 1% Temporary, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution.

Data Scientist - Remote

NAVA Software Solutions

Houston, TX • On-site, Remote

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

NAVA Software solutions is looking for a Data Scientist
Details:
Data Scientist
Location: Houston TX - Remote is ok
Duration: 12 months
Clients want a data scientist who can develop machine learning models to run forecast scenarios. Also, they want this person to be knowledgeable in AWS Cloud technology
A Data Scientist with physical pipeline experience typically specializes in analyzing and optimizing physical infrastructure pipelines, such as those used in the oil and gas industry or transportation networks. Here are some common job duties associated with this role:
  • Data collection and integration: Data scientists with physical pipeline experience gather data from various sources related to the infrastructure pipelines, such as sensors, SCADA (Supervisory Control and Data Acquisition) systems, or IoT devices. They integrate and consolidate the data for analysis and modeling.
  • Pipeline performance analysis: These professionals analyze the performance of physical pipelines by examining data related to flow rates, pressure levels, temperature, corrosion, and other relevant factors. They use statistical techniques and machine learning algorithms to identify patterns, anomalies, and potential issues that may affect pipeline operations.
  • Predictive modeling and maintenance optimization: Data scientists develop predictive models to forecast pipeline performance and detect potential failures or maintenance needs. They utilize historical data, sensor measurements, and other relevant parameters to train models that can predict future events, such as leaks, blockages, or equipment failures. By identifying critical maintenance requirements in advance, they can optimize maintenance schedules and minimize downtime.
  • Risk assessment and mitigation: Data scientists assess risks associated with physical pipelines, such as environmental hazards, security threats, or regulatory compliance. They develop risk assessment models and analyze the impact of different factors on pipeline safety and integrity. Based on these analyses, they propose mitigation strategies to minimize risks and ensure compliance with safety regulations.
  • Optimization of pipeline operations: Data scientists work on optimizing the operational efficiency of physical pipelines. They analyze data to identify areas of improvement, such as reducing energy consumption, optimizing transportation routes, or improving overall system performance. By applying data-driven approaches and algorithms, they provide recommendations to optimize pipeline operations and maximize efficiency.
  • Visualization and reporting: Data scientists with physical pipeline experience create visualizations, reports, and dashboards to communicate their findings and recommendations effectively. They present complex data in a visually understandable format, allowing stakeholders to make informed decisions regarding pipeline maintenance, operations, and risk management.
  • Collaboration with cross-functional teams: These professionals collaborate with engineers, domain experts, operations personnel, and other stakeholders involved in managing physical pipelines. They work together to understand the specific requirements, constraints, and challenges associated with the infrastructure. Effective communication and teamwork are essential to ensure alignment and successful implementation of data-driven solutions.
  • Continuous improvement and innovation: Data scientists keep up with the latest advancements in data science, machine learning, and pipeline technologies. They explore new methodologies, algorithms, and tools to enhance their skills and propose innovative solutions to address pipeline-related challenges.
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About NAVA Software Solutions

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NAVA is a strategic partner for companies seeking to develop or customize software and products. Our team of experts leverages cutting-edge technology and deep industry knowledge to provide customized solutions that drive business success. Whether you're looking to improve your operations, increase efficiency, or bring a new product to market, NAVA has the expertise and resources to help you achieve your goals. Trust us to be your partner in software and product development.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Rocky Hill, CT, US

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