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Data Science Apprentice Jobs in Georgia (NOW HIRING)

Boston Scientific

Mfg Tech IV

Johns Creek, GA · On-site

VISA Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA ... Collect data and perform statistical analysis for process characterization and scrap reduction ...

Boston Scientific

Mfg Tech IV

Johns Creek, GA

VISA Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA ... Collect data and perform statistical analysis for process characterization and scrap reduction ...

Boston Scientific

Mfg Tech IV

Johns Creek, GA

VISA Boston Scientific will not offer sponsorship or take over sponsorship of an employment VISA ... Collect data and perform statistical analysis for process characterization and scrap reduction ...

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How much do data science apprentice jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for data science apprentice in Georgia is $19.26, according to ZipRecruiter salary data. Most workers in this role earn between $15.43 and $21.30 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data science apprentice, and why are they important?

To thrive as a Data Science Apprentice, you need a solid understanding of statistics, programming (often Python or R), and foundational knowledge in data analysis, usually supported by relevant coursework or a degree in a related field. Familiarity with data visualization tools (such as Tableau or Power BI), SQL databases, and machine learning libraries is commonly expected. Curiosity, problem-solving ability, and effective communication help apprentices stand out by enabling them to learn quickly and convey complex findings clearly. Mastering these skills ensures you can contribute to data-driven projects and grow into more advanced roles in the field.

What is a data science apprentice?

A Data Science Apprentice is an entry-level professional who is learning the skills required to become a data scientist, often through a structured apprenticeship program. They work under the guidance of experienced data scientists to gain hands-on experience in analyzing data, building models, and using data science tools and techniques. Apprenticeships typically combine on-the-job training with classroom instruction, allowing apprentices to develop both practical and theoretical knowledge. The goal is to prepare apprentices for a full-time role in data science by the end of the program.

How do data science apprentices typically collaborate with senior data scientists and other departments?

As a Data Science Apprentice, you'll often work closely with senior data scientists through mentorship and project-based tasks. Collaboration usually involves assisting with data cleaning, exploratory analysis, and supporting model development under supervision. You'll also interact with team members from engineering, product, or business departments to understand project goals and present findings. This cross-functional teamwork helps you build both technical and communication skills, preparing you for more independent roles in the future.

What are the most commonly searched types of Data Science jobs in Georgia?

The most popular types of Data Science jobs in Georgia are:

What are popular job titles related to Data Science Apprentice jobs in Georgia?

For Data Science Apprentice jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Data Science Apprentice jobs in Georgia look for?

The top searched job categories for Data Science Apprentice jobs in Georgia are:

What cities in Georgia are hiring for Data Science Apprentice jobs?

Cities in Georgia with the most Data Science Apprentice job openings:

Data Science Apprentice jobs near you
Infographic showing various Data Science Apprentice job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 81% Full Time, 13% Part Time, 1% Temporary, and 4% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $40,065 per year, or $19.3 per hour.

Senior Data Engineer I - QuantumBlack, AI by McKinsey (Critical Industries)

McKinsey & Company

Atlanta, GA • On-site

$101K - $138K/yr

Full-time

Re-posted 29 days ago

McKinsey & Company rating

8.5

Company rating: 8.5 out of 10

Based on 22 frontline employees who took The Breakroom Quiz

20th of 72 rated business consultants

Job description

Do you want to do work that matters, alongside supportive leaders who will help you grow faster than you ever thought possible? Are you a creative problem-solver who is energized by challenges? You've come to the right place.
YOUR IMPACT
You will be a technical owner, designing and leading the implementation of scalable data architectures for cutting-edge AI and agentic systems.
You will lead the development of robust data pipelines, manage secure and governed data environments, and mentor junior colleagues while collaborating with clients and cross-functional teams. You'll tackle impactful challenges and grow as a leader by architecting innovative AI solutions across diverse industries.
You will own and deliver technical workstreams, designing machine learning, agentic, and autonomous AI systems. You'll lead the integration of machine learning, Generative AI capabilities and agentic frameworks into client solutions, designing MLOps/LLMOps-focused architectures for model management, observability, and automated retraining. You will also spearhead the design of complex feature engineering workstreams, ensuring our data assets are not only robust but also optimized for the next generation of AI models.
Your work will help solve some of the most complex and high-impact challenges facing clients across industries. By partnering with QuantumBlack, AI by McKinsey and QuantumBlack Labs teams, you'll lead the creation of innovative enterprise-grade machine learning systems that accelerate AI adoption and solve critical business problems at speed and scale. You will be instrumental in shaping how we build and deploy high-impact AI systems, enabling clients to achieve meaningful, lasting impact through technical innovation.
You'll be based in one of our North American offices as part of our global Data Engineering community. You'll work in cross-functional Agile teams alongside Data Scientists, Machine Learning Engineers, and industry experts, leading the data engineering workstream to deliver AI solutions. Collaborating with clients from data owners to C-level executives, you'll help design impactful solutions that address complex business challenges and build client capabilities.
You should expect your work to include at least some work in critical industries (Government, Defense, Aerospace, Utilities, Oil & Gas) but you will have the ability to serve other industries as well.
You will grow as a technologist and a leader. You'll develop deep expertise at the intersection of technology strategy and business value by addressing diverse architectural challenges. Working with inspiring, multidisciplinary teams, you'll gain a holistic understanding of enterprise AI while collaborating with leading AI and data experts in the industry.
YOUR GROWTH
Driving lasting impact and building long-term capabilities with our clients is not easy work. You are the kind of person who thrives in a high performance/high reward culture - doing hard things, picking yourself up when you stumble, and having the resilience to try another way forward.
In return for your drive, determination, and curiosity, we'll provide the resources, mentorship, and opportunities you need to become a stronger leader faster than you ever thought possible. Your colleagues-at all levels-will invest deeply in your development, just as much as they invest in delivering exceptional results for clients. Every day, you'll receive apprenticeship, coaching, and exposure that will accelerate your growth in ways you won't find anywhere else.
When you join us, you will have:
  • Continuous learning: Our learning and apprenticeship culture, backed by structured programs, is all about helping you grow while creating an environment where feedback is clear, actionable, and focused on your development. The real magic happens when you take the input from others to heart and embrace the fast-paced learning experience, owning your journey.
  • A voice that matters: From day one, we value your ideas and contributions. You'll make a tangible impact by offering innovative ideas and practical solutions, all while upholding our unwavering commitment to ethics and integrity. We not only encourage diverse perspectives, but they are critical in driving us toward the best possible outcomes.
  • Global community: With colleagues across 65+ countries and over 100 different nationalities, our firm's diversity fuels creativity and helps us come up with the best solutions for our clients. Plus, you'll have the opportunity to learn from exceptional colleagues with diverse backgrounds and experiences.
  • World-class benefits: On top of a competitive salary (based on your location, experience, and skills), we provide a comprehensive benefits package to enable holistic well-being for you and your family.

YOUR QUALIFICATIONS AND SKILLS
  • U.S. Citizenship is required for this role (you must be able to be staffed on Critical Industries work which includes Government, Defense, Aerospace, Utilities, etc.)
  • Degree in Computer Science/Engineering, or equivalent experience
  • 5+ years of relevant professional experience in a data engineering role, with experience leading technical workstreams, mentoring junior engineers, and driving the adoption of software engineering best practices within a team
  • Expert-level proficiency in Python and SQL and the ability to work in polyglot environments (Scala, Java) when required by client enterprise systems
  • Strong experience building Agentic AI, Generative AI, Machine Learning, and Business Intelligence systems, including prompt design, retrieval-augmented generation (RAG), embeddings, vector databases, context construction, and output handling in production workflows using modern frameworks (Spark, LangChain, Databricks, Dask, Airflow, Dagster, Kedro, etc.)
  • Ability to lead the implementation of AI features end to end, with sound judgment around model behavior, evaluation, reliability, guardrails, and the trade-offs between quality, latency, and cost
  • Experience implementing robust data security and governance controls, including managing PII/PHI, authentication, and role-based access control (RBAC)
  • Deep knowledge of MLOps/LLMOps including CI/CD for data workflows, automated agent evaluation (LangSmith, Opik, Langfuse), and infrastructure as code (Terraform) across cloud providers (AWS, Azure, GCP)
  • Exceptional time management and ability to own technical workstreams autonomously
  • Experience using coding agents (Cursor, Claude Code, Codex, etc.) is a plus
  • Strong communication skills, both verbal and written, in English and local office language(s)

Please review the additional requirements regarding essential job functions of McKinsey colleagues.
Our unwavering commitment to integrity drives everything we do, guiding us to always act in the best interests of our clients, our people, and the communities we serve.

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