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Drift Jobs in Decatur, GA (NOW HIRING)

GAINSystems

Applied Data Scientist

Atlanta, GA · On-site

Implement model evaluation, drift detection, and monitoring frameworks to ensure reliability across diverse customer environments * Diagnose and resolve model performance issues for individual ...

Further

Senior AI Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time. * Architect and develop high-performance backend services and APIs using Python ...

Saltbox

Field Operations Manager

Atlanta, GA

Diagnose operational drift, identify root causes, and implement fixes the local team can sustain after you leave * Partner with Market Leaders and Location Managers on execution: you bring the ...

Saltbox

Field Operations Manager

Atlanta, GA

Diagnose operational drift, identify root causes, and implement fixes the local team can sustain after you leave * Partner with Market Leaders and Location Managers on execution: you bring the ...

Mindlance

ServiceNow Data Architect

Atlanta, GA · On-site

$61.25 - $78.75/hr

Define standards that prevent model drift, uncontrolled variance, and low-confidence design decisions. Partner with governance and engineering teams to translate standards into enforceable processes ...

MM International

GCP Cloud Security Engineer

Alpharetta, GA · On-site

$54.50 - $72.75/hr

... drift management status Working with resource owners to remediate configuration drifts Defining priorities, coordinating with peer teams, and leading continuous improvement efforts of security tools ...

Headlands Research

PRN Psychometric Rater

Atlanta, GA · On-site

Actively work to maintain consistency in the performance of ratings over time for individual subjects to ensure efficacy and prevent rater drift * Articulate ratings issues to lead physician, study ...

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All JobsDrift JobsDrift Jobs in Decatur, GA

Drift information

See Decatur, GA salary details

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How much do drift jobs pay per hour?

As of Jul 7, 2026, the average hourly pay for drift in Decatur, GA is $21.85, according to ZipRecruiter salary data. Most workers in this role earn between $19.23 and $23.94 per hour, depending on experience, location, and employer.

What is a Drift and what do people in this role do?

A Drift, in most professional contexts, refers to a role associated with the company Drift, which specializes in conversational marketing and sales software. People working at Drift typically help businesses engage website visitors through chatbots, real-time messaging, and automation tools to accelerate sales and improve customer experience. Their responsibilities may include software development, customer support, sales, marketing, or product management, all focused on enhancing digital conversations. Drift employees work to create seamless communication between businesses and their customers, often using AI-driven solutions. The specific duties depend on the exact position within the company.

What are the key skills and qualifications needed to thrive as a Drift Driver, and why are they important?

To thrive as a Drift Driver, you need advanced car control skills, in-depth knowledge of vehicle dynamics, and experience in motorsport, often supported by a valid racing or motorsport license. Mastery of high-performance vehicles, familiarity with safety gear, and understanding of telemetry systems are typically required. Quick decision-making, concentration under pressure, and strong communication with pit crews are standout soft skills in this role. These abilities ensure safety, competitive performance, and effective teamwork in the fast-paced, high-risk environment of drift racing.

What is the difference between Drift vs Chatbot Developer?

AspectDriftChatbot Developer
Primary RoleDesigns and manages live chat and conversational marketing toolsDevelops and programs chatbots for various platforms
Required SkillsCustomer engagement, marketing automation, basic codingProgramming, AI, natural language processing
Work EnvironmentMarketing teams, SaaS companies, customer supportDevelopment teams, AI firms, tech companies
CertificationsMarketing automation, CRM toolsProgramming languages, AI certifications

Drift focuses on live chat and conversational marketing tools used primarily in sales and customer support, while Chatbot Developers create AI-driven chatbots across platforms. Both roles require technical skills, but Drift roles lean more toward marketing automation, whereas Chatbot Developers focus on AI programming and natural language processing.

What are some typical challenges faced by Drift Operators, and how can they effectively address them?

Drift Operators often encounter challenges such as monitoring complex underground mining equipment, ensuring safety protocols are strictly followed, and responding quickly to unexpected issues like equipment malfunctions or hazardous conditions. Effective communication with team members and supervisors is crucial, as is staying current with safety training and operational procedures. Proactively identifying potential hazards and being adaptable in problem-solving are key strategies to excel in this role.
What are popular job titles related to Drift jobs in Decatur, GA? For Drift jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Drift jobs in Decatur, GA look for? The top searched job categories for Drift jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Drift jobs? Cities near Decatur, GA with the most Drift job openings:
Drift jobs near you
Infographic showing various Drift job openings in Decatur, GA as of July 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $45,441 per year, or $21.8 per hour.
Applied Data Scientist

Applied Data Scientist

GAINSystems

Atlanta, GA • On-site

Full-time

Re-posted 6 days ago

Job description

Applied Data Scientist
Applied Research Group - Supply Chain Optimization
About GAINS
GAINS is on a mission to make supply chains smarter, faster, and self-improving, powered by AI. Our decision intelligence platform doesn't just support decisions, it drives them by aligning strategy, planning, and execution across every level of the supply chain. We serve inventory-intensive industries where the stakes are high and the complexity is real, helping customers move from reactive, spreadsheet-driven planning to continuously learning, AI-led operations that deliver measurable results fast. At GAINS, we call it Moving Forward Faster- and it's not a tagline, it's how we're redefining what's possible in driving supply chain decisions.
About the Role
As an Applied Data Scientist on the Applied Research Group at GAINS, you will research, design, build, and deploy production ML models that directly improve supply chain outcomes for enterprise customers. This is a hybrid role that spans the full ML lifecycle-from exploratory analysis and model development through production deployment and ongoing performance tuning. Your work will address core supply chain problems where machine learning delivers measurable business value.
On any given week, you might be designing a new feature engineering approach, running experiments to evaluate alternative modeling techniques, debugging model drift for a specific customer, or building pipeline infrastructure to operationalize a new ML capability. You will collaborate closely with product managers, professional services, software engineers, and customer-facing teams to translate complex supply chain challenges into well-scoped ML solutions.
This is a hands-on IC role with high autonomy and direct impact on customer outcomes and revenue. You will own ML projects end-to-end-the science and the engineering.
A Day in the Life
  • Research, design, and develop machine learning models for supply chain applications that drive measurable improvements in operational efficiency and planning accuracy
  • Perform exploratory data analysis, statistical modeling, and feature engineering on large, complex supply chain datasets to identify signals and improve model performance
  • Design and run experiments to evaluate new modeling approaches, loss functions, feature sets, and hyperparameter configurations-interpreting results and translating findings into production improvements
  • Build and maintain robust ML pipelines that process, clean, and transform data from enterprise supply chain systems (SQL databases, APIs, ERP integrations)
  • Deploy and maintain models in cloud-based production environments, managing the full lifecycle from training through inference and monitoring
  • Implement model evaluation, drift detection, and monitoring frameworks to ensure reliability across diverse customer environments
  • Diagnose and resolve model performance issues for individual customers-investigating data quality, feature behavior, and distributional shifts
  • Partner with product managers, professional services, and engineering teams to understand customer problems and scope ML solutions appropriately
  • Communicate findings, model behavior, trade-offs, and recommendations clearly to both technical and non-technical stakeholders
  • Contribute to the team's technical direction on ML methodology, architecture, tooling, and best practices

Required Qualifications
  • Bachelor's degree in Computer Science, Statistics, Data Science, Engineering, Operations Research, or a related technical field; or equivalent professional experience
  • 3+ years hands-on experience in applied machine learning or data science roles, with models developed and deployed to production
  • Strong Python skills with experience writing clean, maintainable, production-grade ML code
  • 3+ years professional SQL experience, including complex queries against large enterprise datasets
  • Deep understanding of statistical and machine learning methods: gradient boosting (LightGBM, XGBoost, CatBoost), regression, decision trees, clustering, time series techniques, and model evaluation methodology
  • Experience with feature engineering for structured and tabular data, including domain-informed feature design, temporal feature construction, and feature selection techniques
  • Demonstrated ability to design experiments, evaluate model performance rigorously, and iterate on approaches based on empirical results
  • Experience building and maintaining ML pipelines-data ingestion, feature engineering, training, evaluation, deployment
  • Working knowledge of cloud-based ML infrastructure (Azure preferred; AWS or GCP acceptable)
  • Strong communication skills with the ability to explain model behavior, experimental results, and trade-offs to non-technical audiences
  • Self-directed with a track record of owning ML projects end-to-end-from problem formulation through production delivery-with minimal supervision

Preferred Qualifications
  • Master's or PhD in Computer Science, Statistics, Data Science, Engineering, Operations Research, or a related technical field
  • Experience in supply chain, operations, or logistics domains
  • Background in time series modeling, probabilistic methods, or optimization techniques applied to operational problems
  • Familiarity with Databricks, Spark, or similar distributed compute platforms for ML workloads
  • Experience with Azure services: Azure ML, Container Apps, App Configuration, DevOps pipelines
  • Experience working directly with enterprise customers to tune, validate, and explain model outputs in their specific business context
  • Experience with MLflow for experiment tracking and model versioning
  • Experience with Kafka or similar event streaming platforms for real-time data integration
  • Curiosity about the business processes your models serve and motivation to understand how supply chain decisions are actually made

Core Competencies
  • Customer Impact: Builds solutions with the end customer in mind-measures success by business outcomes, not model metrics alone
  • Analytical Depth: Goes beyond surface-level results to understand why models behave the way they do, especially when they fail-combines scientific rigor with practical problem-solving
  • Engineering Rigor: Writes production-quality code, designs reliable pipelines, and thinks about failure modes before they happen
  • Manages Complexity: Navigates messy real-world data and ambiguous problem definitions to deliver practical, scalable solutions
  • Communicates Effectively: Translates technical model behavior and experimental findings into clear narratives for product, services, and leadership audiences
  • Drives Results: Takes ownership, follows through on commitments, and delivers measurable improvements to customer outcomes

Technology Environment
Python, LightGBM, SQL, Azure (Container Apps, ML, DevOps), Databricks, Git/GitHub. Enterprise supply chain platform with SQL Server backends and REST APIs.
Why GAINS
- Work on software that leverages AI and ML to solve real logistics challenges for customers
- Direct impact on developer experience across the entire engineering org
- Collaborative, low-bureaucracy environment where engineers own their work end-to-end
- Competitive compensation and benefits
We are committed to equal employment opportunity and welcome everyone regardless of race, color, ancestry, religion, national origin, age, sex, gender identity, sexual orientation, disability, marital status, domestic partner status, veteran status or medical condition. We encourage people from all backgrounds to apply.

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