Machine Learning Engineer Job Snowflake area,Arizona USA,IT/Tech

A well-funded, fast-growing data-driven company based in Chicago is seeking a Machine Learning Engineer to spearhead its Marketing Intelligence initiatives. This is an exciting opportunity to lead the development of production-grade ML models, collaborate with business stakeholders, and drive insights that impact real-world decisions. The ideal candidate has a deep understanding of machine learning pipelines, data engineering, and a proven track record of scaling models in cloud environments.

Role:

Design, build, and fine-tune ML models to solve complex business problems

Build scalable, cloud-agnostic ML pipelines and workflows

Apply state-of-the-art techniques in deep learning, time-series forecasting, and NLP

Integrate model outputs into Marketing Intelligence systems and dashboards

Collaborate with business leaders to align model outputs with key objectives

Conduct experiments and analyze data to extract actionable insights

Document findings and communicate effectively across technical and non-technical teams

Requirements:

Master’s degree in a quantitative field (preferred)

7+ years of experience in data science and engineering

Strong foundation in statistical modeling, regression, classification, clustering, and causal inference

Expertise in marketing analytics (MMM, Attribution, Propensity Models)

Proficiency in Python, R, and SQL

Familiarity with MLOps tools and platforms (AWS Sage Maker, Google Vertex AI, Azure ML)

Hands-on with frameworks like Scikit-learn, XGBoost, Tensor Flow, and Py Torch

Strong communication skills and a collaborative mindset

Benefits:

Salary range: $150,000 – $180,000/year

401(k) with 75% match up to 7%

Equity/Stock Ownership potential

Comprehensive health and wellness support

Hybrid work environment (3 days/week in Chicago office)

Skills:

machine learning, data science, deep learning, PyTorch, Tensor Flow, Python, R, SQL, MLOps, Airflow, Spark, PySpark, marketing analytics, attribution modeling, MMM, Snowflake, Big Query, Databricks, regression, classification, causal inference

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