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Director Data Science Jobs in Decatur, GA (NOW HIRING)

GAINSystems

Applied Data Scientist

Atlanta, GA · On-site

Applied Data Scientist Applied Research Group - Supply Chain Optimization About GAINS GAINS is on a ... direct impact on customer outcomes and revenue. You will own ML projects end-to-end-the science and ...

Truist

Fraud Data Scientist II

Atlanta, GA

... science solution design, technical delivery, and measurable business outcome. 4. Engage in ... Availability Able to work all hours scheduled, including overtime as directed by manager/supervisor ...

GAINSystems

Applied Data Scientist

Atlanta, GA · On-site

Applied Data Scientist Applied Research Group - Supply Chain Optimization About GAINS GAINS is on a ... direct impact on customer outcomes and revenue. You will own ML projects end-to-end--the science ...

BlackRock

Director - Data Pipeline Engineering

Atlanta, GA

$243.30K/yr

The Director of the Engineering Alternative Data Pipeline Chapter leads a global team of talented ... Qualifications * BS/MS in Computer Science or related field, or equivalent work experience. * A ...

Home Depot

Sr. Data Scientist, Pro CX

Atlanta, GA · On-site

Actively seek out new business opportunities to leverage data science as a competitive advantage ... This position has 0 Direct Reports Travel Requirements: * Typically requires overnight travel less ...

Honeywell

Sr. Director Data & AI Platforms

Atlanta, GA

$64.75 - $86.50/hr

MS or PhD in Computer Science, Machine Learning, Data Engineering, or a related field - or equivalent deep self-directed research and applied experience in AI systems design. * Industrial Domain ...

New

Honeywell

Sr. Director Data & AI Platforms

Atlanta, GA

$64.75 - $86.50/hr

MS or PhD in Computer Science, Machine Learning, Data Engineering, or a related field - or equivalent deep self-directed research and applied experience in AI systems design. * Industrial Domain ...

New

Truist

Data Scientist II (Fraud Strategy)

Atlanta, GA · On-site

Take accountability and ownership of end-to-end data science solution design, technical delivery ... Availability Able to work all hours scheduled, including overtime as directed by manager/supervisor ...

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$52.7K

$151.2K

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How much do director data science jobs pay per year?

As of May 29, 2026, the average yearly pay for director data science in Decatur, GA is $151,208.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,400.00 and $185,000.00 per year, depending on experience, location, and employer.

What is a Director Data Science job?

A Director of Data Science leads a team of data scientists and analysts to drive data-driven decision-making within an organization. They develop strategic initiatives, oversee machine learning and analytics projects, and collaborate with executives to align data efforts with business goals. The role requires expertise in data science, leadership, and communication to translate complex insights into actionable strategies.

What are the key skills and qualifications needed to thrive in the Director Data Science position, and why are they important?

To thrive as a Director Data Science, you need a deep understanding of advanced statistical modeling, machine learning, and data strategy, typically backed by an advanced degree in a quantitative field and significant leadership experience. Proficiency with tools such as Python, R, SQL, cloud data platforms, and familiarity with data governance frameworks and certifications like Certified Analytics Professional (CAP) are common requirements. Outstanding communication, stakeholder management, and team leadership abilities make candidates stand out in this position. These skills ensure the successful translation of complex data insights into actionable business strategies and the effective leadership of high-performing data science teams.

What types of teams and professionals will I collaborate with as a Director Data Science?

As a Director Data Science, you will regularly collaborate with cross-functional teams including business analysts, data engineers, software developers, product managers, and senior executives. Your role often involves translating business goals into data-driven strategies, as well as mentoring and guiding data scientists and analysts on your team. You may also work closely with stakeholders from marketing, operations, and finance to align analytics initiatives with organizational objectives. This collaborative environment fosters innovative solutions and ensures data science efforts have a meaningful impact on overall business performance.
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Director Data Science jobs near you
Applied Data Scientist

Applied Data Scientist

GAINSystems

Atlanta, GA • On-site

Full-time

Posted 28 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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