Job Description

Purpose

Responsible for managing a team of data scientists, architecting complex enterprise data solutions, and delivering maximum business value through advanced analytics. This role will oversee the full data science lifecycle—from model ideation and development to deployment and maintenance—leveraging AWS services (particularly Amazon SageMaker) and modern MLOps best practices.

Key Responsibilities

• Manage and mentor data scientists, fostering continuous learning
• Design end-to-end data solutions for complex problems
• Select appropriate modeling approaches to meet business needs
• Oversee full model lifecycle: development, deployment, and maintenance
• Implement MLOps best practices using AWS services (SageMaker, Step Functions, API Gateway)
• Translate data insights into actionable recommendations
• Communicate complex findings clearly to stakeholders
• Collaborate with software teams to integrate solutions
• Document technical designs and maintain model versioning
• Meet deadlines through effective prioritization
• Evaluate costs of new model designs against projected benefits
• Monitor ongoing model-related costs (computing, storage) and implement efficiencies
• Work with cross-functional teams to forecast resource needs within budget constraints
• Conduct exploratory data analyses for projects and ad-hoc requests
• Stay current with emerging technologies and methodologies
• Travel up to 25% as needed

Education, Experience, and Skills Required

• High School Diploma or GED required
• Bachelor's degree required; an advanced degree in Data Science, Computer Science, or a related discipline is strongly preferred
• At least eight years of recent experience in data science, machine learning, or a related field
• Proficiency in Python, R, SQL, and common data science libraries and frameworks
• Strong understanding of statistical analysis, data mining, and data visualization techniques
• Demonstrated ability to translate complex analytical concepts into actionable business outcomes
• Experience building models from scratch and managing the end-to-end model development lifecycle
• Familiarity with MLOps methodologies, including model monitoring, version control, and CI/CD pipelines
• Strong knowledge of AWS cloud services (especially SageMaker) and exposure to Step Functions, API Gateway, ECS, Docker, ECR, or CDK is highly desirable
• Some background in DevOps principles and tools is a plus
• Experience with cloud platforms (specifically AWS) is highly advantageous
• Experience in successfully leading and coaching data science teams or individuals
• Excellent written and verbal communication skills, with the ability to clearly present technical concepts to non-technical stakeholders

Altec offers a competitive salary that rewards performance and dedication, along with a comprehensive benefits package that includes:

• Medical, Dental, Vision and Prescription Drug Program
• Retirement 401(k) Traditional or Roth Program Options with Company Match
• Vacation and Holidays
• Parental Leave
• Short Term and Long Term Disability Leave
• Flexible Spending Accounts
• Tuition Assistance Program
• Employee Assistance and Mental Health/Substance Abuse Program
• Life Insurance, Accidental Death and Dismemberment Insurance
• Supplemental Insurance including Hospital Indemnity, Critical Illness and Accident Insurance
• Additional Wellness Programs and Rewards Available

Altec Industries, Inc. and its affiliates are equal opportunity employers and maintain affirmative action plans to recruit, retain, develop, and promote qualified individuals without unlawful consideration of race, gender, color, religion, sexual orientation, gender identity, national origin, age, disability, citizenship status, veteran status, or any other characteristic protected by federal, state or local law. Altec strives to maintain a work environment free from unlawful discrimination and harassment, where associates are treated with respect and dignity.

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