About this opportunity
MetAntz lists this Senior Data Scientist opportunity in menlo park, California. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Senior Data Scientist – AI, Machine Learning & Process Intelligence
About Skan.ai
At Skan.ai, we are transforming enterprise operations through AI-powered process intelligence, task mining, and agentic AI. Our platform leverages behavioral analytics, computer vision, and machine learning to understand how work happens across organizations, converting unstructured human-machine interactions into actionable insights that drive operational excellence. Backed by world-class investors and trusted by Fortune 500 companies, we're building the next generation of intelligent enterprise software.
Role Overview
We're looking for a highly hands-on Senior Data Scientist who thrives on solving complex real-world problems with data. This is an individual contributor role where you'll own machine learning models, data pipelines, and production deployments end-to-end. You'll work with large-scale enterprise datasets, troubleshoot production issues, and collaborate closely with engineering and product teams to deliver impactful AI solutions. Beyond technical ownership, you'll mentor junior data scientists through code reviews, technical guidance, and knowledge sharing while remaining deeply involved in hands‑on development.
What You'll Do
Build, train, evaluate, and optimize machine learning models for task detection, behavioral pattern recognition, process mapping, and drift analysis
Own the complete ML lifecycle, including data exploration, feature engineering, model selection, experimentation, validation, and deployment
Design and develop scalable data pipelines for multimodal enterprise data, including event logs, screen telemetry, and structured process data
Process and analyze large datasets using distributed platforms such as Spark, Databricks, or equivalent technologies
Ensure data quality through validation frameworks, drift detection, monitoring, and proactive issue resolution
Investigate and resolve production data and model issues across customer environments
Build internal diagnostic tools and monitoring dashboards for production ML systems
Partner closely with Engineering, Product, Customer Success, and Solutions teams to deliver reliable AI-driven products
Mentor junior data scientists through code reviews, technical guidance, experiment reviews, and best practices
Communicate complex technical concepts and model insights clearly to both technical and non-technical stakeholders
Must-Have Skills
5–8 years of industry experience building and deploying production machine learning solutions
Strong Python programming skills with clean, modular, production-quality code
Hands‑on experience with Spark, Databricks, or other distributed data processing frameworks
Strong expertise in feature engineering, model development, experimentation, and statistical analysis
Experience with at least two of the following: Supervised Learning, Unsupervised Learning, NLP, Deep Learning, Sequence Modeling, or Process Mining
Experience building scalable data pipelines and working with large-scale datasets
Strong understanding of data quality, model monitoring, drift detection, and production troubleshooting
Experience mentoring junior data scientists through technical leadership and code reviews
Excellent problem-solving, debugging, and communication skills
Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related quantitative discipline
Nice to Have
Experience with Process Mining, RPA, Workflow Analytics, or Enterprise Process Intelligence platforms
Familiarity with MLflow, Weights & Biases, or similar experiment tracking platforms
Experience with LLMs, Transformer models, or Multimodal AI systems
Startup or high-growth SaaS product experience
Experience building AI products for enterprise customers
Location
Menlo Park, California, USA
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Worksite address
menlo park, CA, 94029, US
Who can apply
Review the original listing for work authorization, qualifications and employer requirements.