Applied Data Scientist / Machine Learning Engineer (Decision Intelligence)

WorkWave

2d • $160,000 - $170,000 • Hybrid

About The Position

We are looking for a product-minded Applied Data Scientist or Machine Learning Engineer to help build, ship, and scale ML-powered products that directly improve how our customers make decisions, operate their businesses, and serve their own users. This is not a research-only role, nor is it a service-oriented internal analytics position. We want someone who has taken machine learning from problem definition through experimentation, production deployment, measurement, iteration, and long-term ownership. You understand that great models are not just accurate in notebooks—they are usable, explainable, measurable, scalable, and valuable inside a real product. Whether your background leans heavily toward Data Engineering/ML Ops or Applied Data Science, you have a strong bias toward shipping and an interest in bridging both worlds to bring AI to life.

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.
• 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.

Nice To Haves

• Experience with SaaS products is highly valued.
• Experience with decision intelligence, forecasting, customer behavior modeling, workforce/route optimization, or operational intelligence products.
• Experience with LLMs, GenAI, or agentic workflows applied to real product use cases.
• Prior experience acting as a Senior or Lead scientist responsible for guiding technical direction.

Responsibilities

• 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.

Benefits

• health and dental
• 401k with company match
• Flexible Time Off policy or generous PTO plan (role dependent)
• 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

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed