Amazon Model Jobs in Missouri (NOW HIRING)

We currently have a career opportunity for a Lead Data Scientist to join our team .

Job Overview:

As a Lead Technical Consultant you will participate in all aspects of the software development lifecycle which includes estimating, technical design, implementation, documentation, testing, deployment and support of application developed for our clients. As a member working in a team environment you will work with solution architects and developers on interpretation/translation of wireframes and creative designs into functional requirements, and subsequently into technical design.

We are seeking a highly analytical and results-driven Machine Learning Engineer / Data Scientist to develop and deploy predictive models that drive business outcomes and improve decision-making across the organization. The ideal candidate will combine strong machine learning expertise, data engineering skills, and business acumen to translate complex data into actionable insights.

Experience working within client's machine learning and analytics ecosystem, including AWS and dbt, will significantly accelerate onboarding and enable rapid contribution to key initiatives.

Perficient is the global AI and technology consulting firm disrupting the traditional consulting model. Powered by our 7,000+ advisors, engineers, and designers, Perficient implements AI-first solutions that break conventions and deliver outcomes that matter. Proudly serving clients that represent the world's most innovative brands, and in collaboration with our powerful technology partner ecosystem, we bring deep industry expertise and data-driven design to redefine how businesses run and succeed. Perficient is different. For real. Learn more at perficient.com.

• Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, or a related quantitative field.
• 8+ years of experience developing and deploying predictive models using statistical and machine learning techniques.
• Strong experience applying machine learning methodologies to solve business problems and improve organizational outcomes.
• Advanced SQL skills with demonstrated experience querying, transforming, and analyzing large, complex datasets.
• Hands-on experience with AWS cloud services for data storage, processing, and analytics.
• Strong analytical and problem-solving skills with the ability to work independently and collaboratively.
• Excellent verbal and written communication skills and the ability to effectively translate business requirements into data-driven solutions.
• Proven experience partnering with cross-functional stakeholders and delivering actionable insights.
• Passionate coders with 3-5 years of application development experience.
• Client facing or consulting experience highly preferred.
• Skilled problem solvers with the desire and proven ability to create innovative solutions.
• Flexible and adaptable attitude, disciplined to manage multiple responsibilities and adjust to varied environments.
• Future technology leaders- dynamic individuals energized by fast paced personal and professional growth.
• Phenomenal communicators who can explain and present concepts to technical and non-technical audiences alike, including high level decision makers.
• Bachelor's Degree in MIS, Computer Science, Math, Engineering or comparable major.
• Solid foundation in Computer Science, with strong competencies in data structures, algorithms and software design.
• Knowledge and experience in developing software using agile methodologies.
• Proficient in authoring, editing and presenting technical documents.

• Ability to communicate effectively via multiple channels (verbal, written, etc.) with technical and non-technical staff.
   

  Preferred Qualifications

• Experience with Amazon SageMaker for model development, training, and deployment.
• Experience using dbt for data transformation, modeling, and analytics engineering.
• Experience working in healthcare, health insurance, or other highly regulated industries.
• Knowledge of MLOps practices, model monitoring, and cloud-based deployment frameworks.

WHAT WE BELIEVE

At Perficient, we promise to challenge, champion, and celebrate our people. You will experience a unique and collaborative culture that values every voice. Join our team, and you'll become part of something truly special.

We believe in developing a workforce that is as diverse and inclusive as the clients we work with. We're committed to actively listening, learning, and acting to further advance our organization, our communities, and our future leaders... and we're not done yet.

Perficient, Inc. proudly provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, national origin, age, disability, genetic information, marital status, amnesty, or status as a protected veteran in accordance with applicable federal, state and local laws. Perficient, Inc. complies with applicable state and local laws governing non-discrimination in employment in every location in which the company has facilities. This policy applies to all terms and conditions of employment, including, but not limited to, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training. Perficient, Inc. expressly prohibits any form of unlawful employee harassment based on race, color, religion, gender, sexual orientation, national origin, age, genetic information, disability, or covered veterans. Improper interference with the ability of Perficient, Inc. employees to perform their expected job duties is absolutely not tolerated.

Disability Accommodations:

Perficient is committed to providing a barrier-free employment process with reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or accommodation due to a disability, please contact us.

Applications will be accepted until the position is filled or the posting is removed. 

The salary range for this position takes into consideration a variety of factors, including but not limited to skill sets, level of experience, applicable office location, training, licensure and certifications, and other business and organizational needs. The new hire salary range displays the minimum and maximum salary targets for this position across all US locations, and the range has not been adjusted for any specific state differentials. It is not typical for a candidate to be hired at or near the top of the range for their role, and compensation decisions are dependent on the unique facts and circumstances regarding each candidate. A reasonable estimate of the current salary range for this position is $73,008 to $170,640. Please note that the salary range posted reflects the base salary only and does not include benefits or any potential equity or variable bonus programs. Information regarding the benefits available for this position are in our benefits overview. 

Disclaimer:  The above statements are not intended to be a complete statement of job content, rather to act as a guide to the essential functions performed by the employee assigned to this classification.  Management retains the discretion to add or change the duties of the position at any time. 

#LI-RS1

• Develop, validate, deploy, and monitor predictive and machine learning models to solve business challenges and support strategic decision-making.
• Analyze large and complex datasets to identify trends, patterns, and opportunities for optimization.
• Partner with business stakeholders, product owners, and cross-functional teams to understand requirements and deliver data-driven solutions.
• Design and maintain scalable data pipelines and model workflows within cloud-based environments.
• Perform data extraction, transformation, and analysis using advanced SQL techniques.
• Collaborate with engineering and analytics teams to operationalize machine learning solutions and ensure production readiness.
• Communicate analytical findings, model performance, and recommendations to both technical and non-technical audiences.
• Contribute to best practices for data science, modeling, governance, and experimentation.