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Data Science Engineer

Predictive Sales A.I. · Remote · Miami

Job description

Full Time position in 120 E Palmetto Park Road Boca Raton, FL, 33432

Job Title: Data Science Engineer

Location: Boca Raton, FL-Remote/Hybrid

About Us:

At Predictive Sales AI (PSAI), we’re redefining how technology and intelligence transform digital marketing. Our AI-powered software enables home services businesses to make smarter, faster decisions—fueling growth through automation, prediction, and precision.

We are seeking a Data Science Engineer with strong data engineering and MLOps expertise to build scalable, production-grade ML and data platforms that directly impact customer growth and retention. Job Overview:

As a Data Science Engineer, you will design and operate the data + machine learning foundations behind PSAI’s predictive products. You will build scalable pipelines and robust warehouse/lakehouse models across CRM, marketing, product events, and external datasets — ensuring reliability, accuracy, and business continuity at scale.

This role requires:

Key Responsibilities:

  • 4+ years in data-centric engineering

  • Proven experience deploying ML models via pipelines

  • Deep expertise in Python, SQL, and Azure infrastructure

  • Architectural ownership through data contracts and resilient modeling

  • Build scalable batch and near-real-time ingestion pipelines using Azure Data Factory, APIs, event streams, and external connectors.

  • Develop ML-ready datasets across CRM, marketing automation platforms, product telemetry, and geospatial data sources.

  • Design performant, well-modeled warehouse/lakehouse systems in Azure Synapse or Databricks.

  • Train and deploy predictive models (lead scoring, churn prediction, forecasting) through reproducible pipelines.

  • Build time-aware, leakage-resistant feature pipelines for production ML use cases.

  • Support full MLOps lifecycle using Azure Machine Learning, including experiment tracking, model registry, and deployment.

  • Implement automated validation, anomaly detection, reconciliation, and monitoring for pipelines and warehouse models.

  • Design and enforce data contracts to prevent upstream schema changes from breaking downstream ML workflows.

  • Own pipeline SLAs, alerting, incident response, and durable improvements through postmortems.

  • Optimize processing for very large datasets (>100GB) through partitioning, incremental loads, distributed compute, and query tuning.

  • Improve cost efficiency across compute/storage in Azure environments.

  • Maintain clean, testable, production-ready Python codebases using:

  • Object-oriented patterns

  • Type hinting

  • CI/CD workflows via Azure DevOps

  • Package models and pipelines using Docker for consistent deployment across dev/staging/prod.

  • Communicate architectural trade-offs and technical debt in business terms to Product, RevOps, and leadership.

  • Partner with Engineering on instrumentation and scalable data integration.

  • Mentor junior engineers through pairing, code reviews, and documentation best practices.

Desired Traits:

We are looking for an individual who is organized, proactive, and detail-oriented. In this role, you will work closely with teams across the company. Here’s what we’re looking for:

  • Ownership mindset with a reliability-first approach
  • Strong SQL/Python and a high attention to data quality
  • Scales systems thoughtfully (performance/cost aware, maintainable designs)
  • Collaborative communicator across engineering, RevOps, and analytics
  • Documents well and supports others through reviews/mentorship

Required Skills and Experience:

  • Preferred Master’s degree in Data Science, Computer Science, Statistics, Engineering, or a closely related quantitative field.
  • 4+ years in data engineering, ML engineering, or data platform development.
  • Minimum 2 years deploying ML models into production workflows.
  • Experience building pipelines and warehouse systems at scale (>100GB datasets).
  • Demonstrated adaptability in fast-changing technical and business environments.
  • Python (Expert): pandas, polars, scikit-learn; PyTorch, transformers; production engineering (OOP, testing, typing)
  • SQL (Expert): advanced analytics, recursive CTEs, query tuning, Azure Synapse optimization
  • Azure Data & ML Stack: Data Factory (ETL/ELT), Azure ML (MLOps), Key Vault, Databricks/Spark, Docker deployment
  • Distributed & Large-Scale Compute: Spark, Ray, Dask; GPU acceleration with RAPIDS (plus)
  • Geospatial & Specialized Data: GeoPandas, Shapely, rasterio
  • AI Automation & LLMs: LangChain/Semantic Kernel, agentic workflows
  • DevOps & CI/CD: Azure DevOps pipelines, Gitflow, rebasing, clean version control

Why Join Us?

  • Innovative Environment: Be part of a forward-thinking company that values creativity and encourages the exploration of new ideas.
  • Professional Growth: Access opportunities for continuous learning and career advancement within a supportive and dynamic team.
  • Comprehensive Benefits: Enjoy a competitive salary, performance-based bonuses, flexible work arrangements, and a robust benefits package.
  • Collaborative Culture: Work in a team-oriented environment where collaboration and mutual respect drive our success.

If you're ready to be part of an innovative, growth-oriented team, apply today!

Hours

40

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