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Algorithmic Trader Jobs in Georgia (NOW HIRING)

Smarsh

Lead Data Scientist

Atlanta, GA · On-site

... algorithms. * Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade ...

Logility

Client Executive - Midwest

Atlanta, GA · On-site +1

$73K - $100K/yr

... AI-driven algorithms, and machine learning to help deliver integrated planning and operations ... Logility is a publicly traded company (NASDAQ: LGTY). Learn more at JOB RESPONSIBILITIES: Our ...

FIS

Senior Intellectual Property Counsel

Atlanta, GA · On-site +1

Provide legal oversight on responsible AI practices, including data usage, algorithmic risk, model ... Counsel on issues involving patents , trade secrets , copyrights, open-source software , software ...

ZYWIE INC

Field Sales Support Specialist

Duluth, GA · On-site

... by algorithms to provide insights into a patient's heart rhythm and potential cardiac conditions ... Attend trade shows and other company-sponsored events to promote products and generate leads.

ASSA ABLOY

Regional Sales Manager

Peachtree City, GA · On-site

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

BlackRock, Inc.

Associate

Atlanta, GA · On-site

$135K - $148K/yr

Contribute to development of Aladdin's global, multi-asset trading platform. Architect and drive ... Algorithms, Optimization, or related quantitative processes; Relational databases; and Financial or ...

ASSA ABLOY

Regional Sales Manager

Kennesaw, GA · On-site

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

BlackRock

Associate

Atlanta, GA

$135K - $148K/yr

Contribute to development of Aladdin's global, multi-asset trading platform. Architect and drive ... Algorithms, Optimization, or related quantitative processes; Relational databases; and Financial or ...

ICONMA

FSE Senior AI Enginee

Atlanta, GA · On-site

$117K - $155K/yr

... trade-off, regularization (L1/L2, dropout) • Unsupervised Learning: Clustering: K-Means, DBSCAN ... algorithms - Adjacent & advanced techniques: Transfer learning and fine-tuning pre-trained models ...

ASSA ABLOY

Regional Sales Manager

Austell, GA · On-site

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

ASSA ABLOY

Regional Sales Manager

Norcross, GA

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

ASSA ABLOY

Regional Sales Manager

Austell, GA · On-site

Underpinned by a unique biometric algorithm, Biosite provides market-leading software solutions for ... Working closely with new customers to build successful trading relationships. * Developing your own ...

JLL

Lead AI Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Whether you've got deep experience in commercial real estate, skilled trades or technology, or you ... Experience in AI agent orchestration, planning algorithms, and decision-making frameworks

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All JobsAlgorithmic Trader JobsAlgorithmic Trader Jobs in Georgia

Algorithmic Trader information

See Georgia salary details

$33.4K

$81.7K

$227.6K

How much do algorithmic trader jobs pay per year?

As of Jul 3, 2026, the average yearly pay for algorithmic trader in Georgia is $81,714.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,700.00 and $89,100.00 per year, depending on experience, location, and employer.

How much do algorithmic traders make?

Algorithmic traders typically earn between $80,000 and $200,000 annually, with experienced professionals and those working at hedge funds or proprietary trading firms earning higher salaries and bonuses. Compensation often depends on skill level, trading performance, and the firm's size, with many traders also receiving performance-based incentives.

What are the key skills and qualifications needed to thrive as an Algorithmic Trader, and why are they important?

To thrive as an Algorithmic Trader, you need a strong background in mathematics, statistics, programming (often Python, C++, or R), and a solid understanding of financial markets, usually supported by a relevant degree. Familiarity with trading platforms, backtesting frameworks, and data analysis tools, plus certifications like CFA or FRM, are commonly required. Strong analytical thinking, attention to detail, and the ability to work under pressure are vital soft skills for success in this fast-paced environment. These skills enable traders to develop effective, automated strategies that capitalize on market opportunities while managing risk efficiently.

What are some typical challenges faced by algorithmic traders in their day-to-day work?

Algorithmic traders often encounter challenges such as maintaining and updating trading algorithms to adapt to rapidly changing market conditions, ensuring low-latency execution, and managing the risks associated with automated trading. Collaborating closely with quantitative analysts, software engineers, and risk managers is essential to refine strategies and troubleshoot technical issues. Staying compliant with regulatory requirements and monitoring for unexpected market behaviors or system errors are also important aspects of the role.

What is an algorithmic trader?

An algorithmic trader is a financial professional who uses computer algorithms to automate trading strategies in financial markets. These traders develop, test, and implement mathematical models that analyze market data and execute trades at speeds and frequencies impossible for humans. Algorithmic traders work in environments such as investment banks, hedge funds, and proprietary trading firms, and their goal is often to maximize returns while managing risk. They typically need strong skills in programming, quantitative analysis, and finance.

Is algo trading a good career?

Algorithmic trading is a specialized career that involves developing and implementing automated trading strategies using programming skills and quantitative analysis. It can be financially rewarding and offers opportunities in finance firms and hedge funds, but it requires strong technical knowledge, risk management skills, and continuous learning. Success depends on market conditions, technical proficiency, and the ability to adapt strategies over time.

Who is the richest Algo trader in the world?

The richest algorithmic trader is often considered to be Jim Simons, founder of Renaissance Technologies, a highly successful quantitative hedge fund. His firm employs advanced mathematical models and computer algorithms to generate trading strategies, making him one of the wealthiest individuals in the trading industry. Many top algo traders leverage skills in mathematics, programming, and data analysis to succeed in this field.

Is algo trading really profitable?

Algorithmic traders use automated systems and algorithms to execute trades based on predefined criteria. While successful algo trading can be profitable, it requires advanced programming skills, market knowledge, and risk management; profitability varies depending on strategy, market conditions, and execution quality.

What is the difference between Algorithmic Trader vs Quantitative Analyst?

AspectAlgorithmic TraderQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skillsDegree in mathematics, statistics, or finance; strong analytical skills
Work EnvironmentTrading firms, hedge funds, financial institutions; fast-pacedFinancial institutions, research firms; analytical and research-focused
Employer & Industry UsageUsed primarily in trading and investment firmsUsed in asset management, hedge funds, and investment banks

While both roles require strong quantitative skills and programming knowledge, Algorithmic Traders focus on developing and executing trading algorithms in real-time markets, whereas Quantitative Analysts primarily develop models and strategies for investment decision-making. The roles often overlap but differ mainly in their focus on trading execution versus model development.

What are popular job titles related to Algorithmic Trader jobs in Georgia? For Algorithmic Trader jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Algorithmic Trader jobs in Georgia look for? The top searched job categories for Algorithmic Trader jobs in Georgia are:
Algorithmic Trader jobs near you
Lead Data Scientist

Lead Data Scientist

Smarsh

Atlanta, GA • On-site

Full-time

Posted 16 days ago

Job description

Who are we?

Smarsh empowers its customers to manage risk and unleash intelligence in their digital communications. Our growing community of over 6500 organizations in regulated industries counts on Smarsh every day to help them spot compliance, legal or reputational risks in 80+ communication channels before those risks become regulatory fines or headlines.  Relentless innovation has fueled our journey to consistent leadership recognition from analysts like Gartner and Forrester, and our sustained, aggressive growth has landed Smarsh in the annual Inc. 5000 list of fastest-growing American companies since 2008.

Summary
 
As a Lead Data Scientist (NLP & Financial Compliance) at Smarsh, you will spearhead the development of state-of-the-art natural language processing (NLP) and large language model (LLM) solutions that power next-generation compliance and surveillance systems. You'll work on highly specialized problems at the intersection of natural language processing, communications intelligence, financial supervision, and regulatory compliance, where unstructured data from emails, chats, voice transcripts, and trade communications hold the keys to uncovering misconduct and risk.
 
The role will involve working with other Senior Data Scientists and mentoring Associate Data Scientists in analyzing complex data, generating insights, and creating solutions as needed across a variety of tools and platforms. This role demands both technical excellence in NLP modeling and a deep understanding of financial domain behavior-including insider trading, market manipulation, off-channel communications, MNPI, bribery, and other supervisory risk areas. The ideal candidate for this position will possess the ability to perform both independent and team-based research and generate insights from large data sets with a hands-on/can do attitude of servicing/managing day to day data requests and analysis.
 
This role also offers a unique opportunity to get exposure to many problems and solutions associated with taking machine learning and analytics research to production. On any given day, you will have the opportunity to interface with business leaders, machine learning researchers, data engineers, platform engineers, data scientists and many more, enabling you to level up in true end-to-end data science proficiency.
How will you contribute?
  • Collect, analyze, and interpret small/large datasets to uncover meaningful insights to support the development of statistical methods / machine learning algorithms.
  • Lead the design, training, and deployment of NLP and transformer-based models for financial surveillance and supervisory use cases (e.g., misconduct detection, market abuse, trade manipulation, insider communication).
  • Development of machine learning models and other analytics following established workflows, while also looking for optimization and improvement opportunities
  • Data annotation and quality review 
  • Exploratory data analysis and model fail state analysis 
  • Contribute to model governance, documentation, and explainability frameworks aligned with internal and regulatory AI standards.
  • Client/prospect guidance in machine learning model and analytic fine-tuning/development processes
  • Provide guidance to junior team members on model development and EDA
  • Work with Product Manager(s) to intake project/product requirements and translate these to technical tasks within the team's tooling, technique and procedures
  • Continued self-led personal development
What will you bring?
  • Strong understanding of financial markets, compliance, surveillance, supervision, or regulatory technology
  • Experience with one or more data science and machine/deep learning frameworks and tooling, including scikit-learn, H2O, keras, pytorch, tensorflow, pandas, numpy, carot, tidyverse
  • Command of data science and statistics principles (regression, Bayes, time series, clustering, P/R, AUROC, exploratory data analysis etc...)
  • Strong knowledge of key programming concepts (e.g. split-apply-combine, data structures, object-oriented programming)
  • Solid statistics knowledge (hypothesis testing, ANOVA, chi-square tests, etc...)
  • Knowledge of NLP transfer learning, including word embedding models (gloVe, fastText, word2vec) and transformer models (Bert, SBert, HuggingFace, and GPT-x etc.)
  • Experience with natural language processing toolkits like NLTK, spaCy, Nvidia NeMo
  • Knowledge of microservices architecture and continuous delivery concepts in machine learning and related technologies such as helm, Docker and Kubernetes
  • Familiarity with Deep Learning techniques for NLP.
  • Familiarity with LLMs - using ollama & Langchain
  • Excellent verbal and written skills
  • Proven collaborator, thriving on teamwork
 
Preferred Qualifications
  • Master's or Doctor of Philosophy degree in Computer Science, Applied Math, Statistics, or a scientific field
  • Familiarity with cloud computing platforms (AWS, GCS, Azure)
  • Experience with automated supervision/surveillance/compliance tools
$166,000 - $214,000 a year
 
The above salary range represents Smarsh's good faith and reasonable estimate of the range of possible base compensation at the time of posting. Any applicable bonus programs will be discussed during the recruiting process.
 
The salary for this role will be set based on a variety of factors, including but not limited to, internal equity, experience, education, location, specialty and training.
 
Local cost of living assessments are done for each new hire at the time of offer.
About our culture

Smarsh hires lifelong learners with a passion for innovating with purpose, humility and humor. Collaboration is at the heart of everything we do. We work closely with the most popular communications platforms and the world's leading cloud infrastructure platforms. We use the latest in AI/ML technology to help our customers break new ground at scale. We are a global organization that values diversity, and we believe that providing opportunities for everyone to be their authentic self is key to our success. Smarsh leadership, culture, and commitment to developing our people have all garnered Comparably.com Best Places to Work Awards. Come join us and find out what the best work of your career looks like.
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