Machine Learning Engineer/Predictive Analyst
Listed on 2026-05-24
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IT/Tech
Data Analyst, Machine Learning/ ML Engineer, Data Scientist, AI Engineer
Machine Learning Engineer / Predictive Analytics Consultant Preferred Locations
Birmingham, AL or Dallas, TX
Position OverviewWe are seeking a hands‑on Machine Learning Engineer / Predictive Analytics Consultant to join an established machine learning team focused on scaling predictive analytics capabilities across the business. This role will support high‑impact initiatives primarily focused on sales and marketing forecasting, predictive modeling, and business intelligence transformation efforts.
The organization has already built out a mature cloud and big data environment and is now focused on increasing delivery capacity, accelerating project timelines, and expanding the team's ability to support growing business demand. This individual will help transition the business beyond traditional dashboarding and reporting into forward‑looking predictive analytics and forecasting solutions.
This is a highly collaborative but autonomous role requiring someone who can operate with minimal guidance, solve complex business problems independently, and deliver practical machine learning solutions at enterprise scale.
Key Responsibilities- Design, build, test, and deploy machine learning and predictive analytics models using large‑scale structured and unstructured datasets
- Develop forecasting and predictive modeling solutions supporting sales, marketing, and operational business initiatives
- Partner directly with business stakeholders to translate ambiguous business requests into actionable data solutions
- Perform exploratory data analysis, feature engineering, model selection, validation, tuning, and performance optimization
- Work with existing enterprise‑scale cloud and big data environments to support scalable analytics initiatives
- Help increase team throughput by accelerating project delivery and supporting a growing backlog of analytics requests
- Collaborate with cross‑functional teams including analytics, engineering, and business leadership
- Communicate analytical findings and model outcomes clearly to both technical and non‑technical stakeholders
- Contribute to ongoing improvements in predictive analytics processes, scalability, and operational efficiency
- 5+ years of experience in Machine Learning, Predictive Analytics, Data Science, or related data‑focused roles
- Strong hands‑on experience with:
- Python
- SQL
- Spark / PySpark (Nice to have)
- Snowflake (Nice to have)
- Experience building machine learning and predictive models from the ground up
- Experience working with large‑scale datasets and distributed data processing environments
- Strong understanding of statistical analysis, forecasting, predictive modeling, and machine learning methodologies
- Experience operating within cloud‑based analytics ecosystems (AWS, Azure, or GCP)
- Proven ability to work independently with minimal direction
- Strong analytical thinking and problem‑solving skills
- Ability to translate business problems into scalable technical solutions
- Experience supporting sales and marketing analytics initiatives
- Experience with forecasting and business performance prediction models
- Experience working in enterprise‑scale machine learning environments
- Exposure to Databricks or similar modern data platforms
- Experience communicating directly with business stakeholders and leadership teams
The ideal candidate is not someone who simply executes assigned tasks. We are looking for a proactive problem solver who can independently identify opportunities, work through ambiguity, and deliver practical machine learning solutions that drive measurable business value. This individual should be comfortable operating in a fast‑paced environment with evolving priorities and growing demand for predictive analytics capabilities.
Compensation and BenefitsDetermining compensation for this role (and others) at Vaco/Highspring depends upon a wide array of factors including but not limited to:
- the individual's skill sets, experience and training;
- licensure and certification requirements;
- office location and other geographic considerations;
- other business and organizational needs.
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