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 problemsBuild scalable, cloud-agnostic ML pipelines and workflowsApply state-of-the-art techniques in deep learning, time-series forecasting, and NLPIntegrate model outputs into Marketing Intelligence systems and dashboardsCollaborate with business leaders to align model outputs with key objectivesConduct experiments and analyze data to extract actionable insightsDocument findings and communicate effectively across technical and non-technical teamsRequirements:
Master's degree in a quantitative field (preferred)7+ years of experience in data science and engineeringStrong foundation in statistical modeling, regression, classification, clustering, and causal inferenceExpertise in marketing analytics (MMM, Attribution, Propensity Models)Proficiency in Python, R, and SQLFamiliarity with MLOps tools and platforms (AWS SageMaker, Google Vertex AI, Azure ML)Hands-on with frameworks like Scikit-learn, XGBoost, TensorFlow, and PyTorchStrong communication skills and a collaborative mindsetBenefits:
Salary range: $150,000 – $180,000/year401(k) with 75% match up to 7%Equity/Stock Ownership potentialComprehensive health and wellness supportHybrid work environment (3 days/week in Chicago office)Skills:
machine learning, data science, deep learning, PyTorch, TensorFlow, Python, R, SQL, MLOps, Airflow, Spark, PySpark, marketing analytics, attribution modeling, MMM, Snowflake, BigQuery, Databricks, regression, classification, causal inference
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