The Leader in Cloud-Based Field Service and Fleet Management Solutions for Companies With a Mobile Workforce.
Applied Data Scientist / Machine Learning Engineer – Decision Intelligence
Location
United States
Posted
1 day ago
Salary
$160K - $170K / year
Seniority
Senior
Job Description
Applied Data Scientist / Machine Learning Engineer – Decision Intelligence
WorkWave
• Drive the development of machine learning capabilities (forecasting, recommendation, ranking, optimization, or decision intelligence) powering customer-facing SaaS products. • Design reliable data and feature pipelines alongside models from discovery through experimentation, validation, deployment, and monitoring. • Partner with Product Managers and Software Engineers to embed ML directly into product workflows, user experiences, and decision-making tools. • Move quickly from prototype to production while balancing accuracy, interpretability, latency, maintainability, and business impact. • Define offline and online evaluation strategies, including model quality, drift, and reliability. Design A/B tests and causal measurement frameworks to prove ML features improve customer outcomes. • Collaborate with Data teams to ensure models are supported by high-quality features, while building feedback loops so product experiences improve over time. • Help manage and optimize cloud data infrastructure, ensuring trustworthy insights and proactively managing data health before it impacts users. • Bring strong judgment around when to use traditional ML, statistical modeling, LLMs, heuristics, or simpler product logic. Make practical trade-offs across model complexity and customer impact. • Clearly communicate what ML can and cannot solve to influence roadmap decisions, helping identify where machine learning can create true product differentiation. • Guide and mentor other data scientists, ML engineers, analysts, and cross-functional partners in applied ML best practices.
Job Requirements
- 3+ years (ideally 5+) of professional experience in applied data science, machine learning, or ML engineering, including hands-on experience building and shipping models into production products. Experience with SaaS products is highly valued.
- Strong Python skills and hands-on experience with applied ML libraries and frameworks (e.g., Scikit-Learn, XGBoost, PyTorch, TensorFlow). Solid SQL expertise is required.
- Strong understanding of supervised learning, forecasting, ranking, recommendation systems, optimization, or statistical modeling. Experience with real-world, imperfect product datasets is essential.
- Familiarity with MLOps concepts (model versioning, feature pipelines, orchestration via Airflow/dbt/Dagster, monitoring, drift detection) and modern data platforms (e.g., Snowflake, BigQuery, Redshift, Databricks).
- Hands-on experience operating within cloud environments (AWS, GCP, or Azure).
- Excellent communication skills with the ability to explain complex technical trade-offs clearly to product, engineering, and non-technical business stakeholders.
Benefits
- Employees can expect a robust benefits package, including health and dental and 401k with company match
- Find your perfect work/life balance with our Flexible Time Off policy or generous PTO plan (role dependent) and paid holidays
- Up to 4 weeks paid bonding leave
- Tuition reimbursement
- Robust Employee Assistance Program through TotalCare offering free counseling 24/7/365, plus financial counseling, legal guidance, adoption assistance services and much more!
- 24/7 access to virtual medical care with Teladoc
- Quarterly awards based on peer nominations
- Regional discounts and perks
- Opportunities to participate in charitable events and give back to the community
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