Mid Level Data Science Consultant Jobs
Mid level data science consultant jobs go to professionals ready to own analytical workstreams end to end, guide junior analysts, and shape client recommendations with limited oversight. Across on-site, remote, and hybrid settings in Distribution & Wholesale and Consulting & Professional Services, employers like Amazon Web Services and ZS are hiring at this level now.
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DESCRIPTION
Possessing a deep understanding of AWS products and services, as a Delivery Consultant you will be proficient in architecting complex, scalable, and secure solutions tailored to meet the specific needs of each customer. You’ll work closely with stakeholders to gather requirements, assess current infrastructure, and propose effective migration strategies to AWS. As trusted advisors to our customers, providing guidance on industry trends, emerging technologies, and innovative solutions, you will be responsible for leading the implementation process, ensuring adherence to best practices, optimizing performance, and managing risks throughout the project.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides assistance through a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
Key job responsibilities
As an experienced technology professional, you will be responsible for:
- Designing, implementing, and building complex, scalable, and secure GenAI and ML applications and models built on AWS tailored to customer needs
- Providing technical guidance and implementation support throughout project delivery, with a focus on using AWS AI/ML services
- Collaborating with customer stakeholders to gather requirements and propose effective model training, building, and deployment strategies
- Acting as a trusted advisor to customers on industry trends and emerging technologies
- Sharing knowledge within the organization through mentoring, training, and creating reusable artifacts
About the team
About AWS:
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneeredcloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companiestrust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
- 7+ years of technical specialist, design and architecture experience
- 5+ years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience
- 7+ years of consulting, design and implementation of serverless distributed solutions experience
- 5+ years of software development with object oriented language experience
- 3+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- 7+ years of external or internal customer facing, complex and large scale project management experience
- 5+ years of cloud architecture and solution implementation experience
- Bachelor's degree, or 7+ years of professional or military experience
- 8+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- 5+ years of experience hosting and deploying GenAI/ML solutions (e.g., for data pre-processing, training, deep learning, fine tuning, and inferences) or/and Data Science Experience
- 8+ years of coding, data querying languages (e.g. SQL), scripting languages (e.g. Python)
PREFERRED QUALIFICATIONS
- degree in advanced technology, or AWS Professional level certification
- Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
- Knowledge of security and compliance standards including HIPAA and GDPR
- Experience in performance optimization and cost management for cloud environments
- Experience communicating technical concepts to diverse audiences in pre-sales environments
- PhD or Masters of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)
- Knowledge of AWS platform and tools or equivalent cloud experience. Ideally, the candidate has AWS Experience with a proficiency in a wide range of AWS services (e.g. SageMaker, Bedrock, EMR, S3, OpenSearch Service, Step Functions, Lambda, and EC2)
- AWS Professional level certifications (e.g., Solutions Architect Professional, DevOps Engineer Professional, Machine Learning Specialty) preferred
- Hands on experience with deep learning (e.g., CNN, RNN, LSTM, Transformer), machine learning, CV, GNN, or distributed training
- Experience with Data Analytics, Data Engineering, Coding, Automation and Scripting (e.g., Terraform, Python)
- Strong communication skills with the ability to explain technical concepts to both technical and non-technical audiences
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, San Francisco - 176,600.00 - 239,000.00 USD annually
USA, TX, Dallas - 153,600.00 - 207,800.00 USD annually
USA, WA, Seattle - 153,600.00 - 207,800.00 USD annually
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Who's Hiring


Top Industries Hiring
- Distribution & Wholesale
- Consulting & Professional Services
Mid Level Data Science Consultant Jobs: Frequently Asked Questions
How do I get a mid level data science consultant job?
Position your existing experience around ownership and impact rather than task completion. Highlight projects where you led the analytical approach, defined methodology, or delivered findings directly to stakeholders. Emphasize tools you use independently, any mentorship you have provided, and measurable outcomes you drove. Applications that show consultative thinking and end-to-end project accountability stand out at this level.
Which companies hire mid level data science consultants?
Companies hiring mid level data science consultants right now include Amazon Web Services and ZS, based on current listings on Migrate Mate as of November 2026. Hiring at this level comes from a wide range of employers, including management consulting firms, technology companies, and large enterprises building or scaling internal data practices.
Are there remote mid level data science consultant jobs?
Yes, remote and hybrid options are well represented at this experience level. About 100% of mid level data science consultant openings are remote or hybrid as of November 2026, reflecting the project-based and client-facing nature of consulting work that can often be performed without a fixed office location.
How do I move up to a mid level data science consultant role?
Moving from entry level to mid level takes deliberate depth-building over time. Focus on completing full project cycles, not just assigned tasks, and seek opportunities to present findings to stakeholders. Develop stronger command of core tools, pick up adjacent skills like data engineering or business communication, and document the measurable impact of your work so you can speak to it clearly when the time comes.
Which industries hire the most mid level data science consultants?
Mid Level data science consultant roles concentrate in Distribution & Wholesale and Consulting & Professional Services, based on current listings on Migrate Mate as of November 2026. These sectors drive hiring at this level because they generate complex, high-volume data problems that benefit from consultants who can work independently and translate analysis into actionable business decisions.