Data Scientist

Robotics Technologies; Lansing (MI); On-site; USD 140,000 - 190,000; Full time

Job summary

Robotics Technologies LLC in the United States is seeking a Data Scientist to own our machine learning sales forecasting capability end to end. You will design, build, and productionize forecasting models that drive planning, inventory, and revenue decisions across the business, leveraging BigQuery and Vertex AI.

You will engineer features in SQL, train and deploy models, monitor performance, and partner with Sales, Finance, and Operations to translate business questions into forecasting

Qualifications

• 8+ years of experience as a Data Scientist or ML Engineer, proven production deployments.
• Strong time series or demand forecasting background.
• Proficiency in Python and SQL in large-scale environments.

Responsibilities

• Build, validate, and deploy ML-based sales forecasting models (time series, regression, demand forecasting).
• Engineer training data in BigQuery with reusable SQL/transformation layers.
• Train, tune, and deploy models on Vertex AI with custom training jobs and pipelines.
• Stand up model monitoring, retraining triggers, and drift/accuracy tracking in production.
• Collaborate with Sales, Finance, and Operations to translate questions into forecasts.

Skills

Python

SQL

Time series forecasting

BigQuery

Vertex AI

MLOps

Model deployment

Pandas / scikit-learn

Tools

BigQuery

Vertex AI

BQML

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

Work Authorization:US Citizen, Green Card, OPT-EAD, CPT, H-1B, H4-EAD, Other

Job Description:

We're looking for a Data Scientist to own our machine learning sales forecasting capability end to end. You'll design, build, and productionize forecasting models that drive planning, inventory,and revenue decisions across the business. Our data lives in BigQuery and our models are trained, served, and monitored on Vertex AI — so you'll be working with a modern, fully managed Google Cloud stack from day one.

What you'll do:

• Build, validate, and deploy ML-based sales forecasting models (time series, regression, and hierarchical/demand forecasting approaches) that produce accurate short- and long-horizon predictions.
• Engineer features and prepare training data directly in BigQuery, including building reusable, well-documented SQL/transformation layers.
• Train, tune, and deploy models on Vertex AI — using custom training jobs, Vertex AI Pipelines for repeatable workflows, and endpoints (or batch prediction) for serving.
• Stand up model monitoring, retraining triggers, and drift/accuracy tracking so forecasts stay reliable in production.
• Partner with Sales, Finance, and Operations stakeholders to translate business questions into forecasting problems and communicate results clearly to non-technical audiences.
• Establish forecast accuracy benchmarks (e.g., MAPE, WAPE, bias) and continuously improve on them.
• Contribute to data quality, documentation, and MLOps best practices across the team.

What we're looking for:

• 8+ years of experience as a Data Scientist or ML Engineer, with hands-on work shipping models to production.
• Strong experience with time series and/or demand forecasting methods.
• Proficiency in Python (pandas, scikit-learn, and a forecasting or deep learning library such as statsmodels, Prophet, XGBoost, or TensorFlow/PyTorch).
• Advanced SQL and real experience working in BigQuery at scale.
• Experience with BigQuery ML (BQML) for in-warehouse model training.
• Hands-on experience with Vertex AI (custom training, pipelines, model registry, endpoints, or batch prediction) or comparable cloud ML platforms with a clear willingness to work in Vertex.
• MLOps experience: CI/CD for models, Vertex AI Pipelines, experiment tracking, automated retraining.
• Solid grounding in model evaluation, validation, and the statistics behind forecasting.
• Ability to explain technical trade-offs and results to business stakeholders.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.