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Applied Data Scientist / Machine Learning Engineer (Decision Intelligence)

3 hours, 55 minutes ago
United States
Full-time
Senior
Data Scientist
Data Science and Analytics
Apache Airflow AWS Azure Dagster Databricks dbt GCP Generative AI LLM Machine Learning MLOps Python PyTorch Scikit-learn Snowflake SQL TensorFlow XGBoost
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WorkWave

WorkWave

WorkWave provides field service management software solutions to automate business operations, improve efficiency, and enhance customer experiences through a suite of products like PestPac® and WorkWave Service™.

Professional Services
251-1K
Founded 1984
View All Jobs 16

Description

  • Own the end-to-end development of machine learning capabilities for customer-facing SaaS products.
  • Design and maintain data and feature pipelines from discovery through experimentation, validation, deployment, and monitoring.
  • Partner with Product Managers and Software Engineers to integrate ML into product workflows and user experiences.
  • Prototype quickly and move solutions into production while balancing accuracy, interpretability, latency, maintainability, and business impact.
  • Define offline and online evaluation strategies, including model quality, drift, reliability, A/B tests, and causal measurement frameworks.
  • Work with data teams to improve data quality and build feedback loops that strengthen product performance over time.
  • Help manage and optimize cloud data infrastructure and MLOps practices to support trustworthy insights and model health.
  • Apply judgment to choose between traditional ML, statistical modeling, LLMs, heuristics, or simpler product logic.
  • Communicate ML trade-offs clearly to influence roadmap decisions and identify opportunities for product differentiation.
  • Mentor data scientists, ML engineers, analysts, and cross-functional partners on applied ML best practices.

Requirements

  • 3+ years, ideally 5+, of professional experience in applied data science, machine learning, or ML engineering.
  • Hands-on experience building and shipping models into production products; SaaS product experience is highly valued.
  • Strong Python skills and hands-on experience with ML libraries and frameworks such as Scikit-Learn, XGBoost, PyTorch, or TensorFlow.
  • Solid SQL expertise is required.
  • Strong understanding of supervised learning, forecasting, ranking, recommendation systems, optimization, or statistical modeling.
  • Experience working with real-world, imperfect product datasets.
  • Familiarity with MLOps concepts such as model versioning, feature pipelines, orchestration, monitoring, and drift detection.
  • Experience with orchestration tools such as Airflow, dbt, or Dagster and data platforms such as Snowflake, BigQuery, Redshift, or Databricks.
  • Hands-on experience in cloud environments such as AWS, GCP, or Azure.
  • Excellent communication skills with the ability to explain technical trade-offs to product, engineering, and non-technical stakeholders.
  • Preferred experience with decision intelligence, forecasting, customer behavior modeling, workforce or route optimization, or operational intelligence products.
  • Preferred experience with LLMs, GenAI, or agentic workflows applied to real product use cases.
  • Preferred prior experience as a Senior or Lead scientist guiding technical direction.

Benefits

  • Remote-first global work environment with flexibility to work virtually or in the office.
  • Health and dental insurance plus a 401(k) with company match.
  • Flexible Time Off policy or generous PTO plan, depending on role, plus paid holidays.
  • Up to 4 weeks of paid bonding leave.
  • Tuition reimbursement.
  • 24/7 employee assistance program with free counseling, financial counseling, legal guidance, and adoption assistance.
  • 24/7 virtual medical care through Teladoc.
  • Regional discounts, perks, and opportunities to participate in charitable events.

Interested in this position?

Apply directly on the company website

Apply Now

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