Jobot
Urgently hiring Senior Data Scientist!
Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.
This Jobot Job is hosted by: Kendall Kaing Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume. Salary: $80,000 - $130,000 per year
A bit about us:
Are you interested in working for the world's largest cannabis market with a footprint that covers the entire breadth of the state of California? Are you someone who wants to be part of the growth of a fast-growing industry? At client company, our mission is clear: to provide the ultimate one stop shop cannabis experience by offering exceptional customer service and diversified products. We strive to build long-term customer loyalty. We’re building a consumer-centric organization that is focused on sharing the transformational potential of cannabis with the world.
Our product line is one of the best-selling cannabis brands in the market today and has claimed the title of the best-selling vape brand across all BDSA-tracked markets and best-selling brand overall in the California market! We are rooted in California and have expanded our operations across the United States, with even more growth on the horizon! Additionally, we’re building distribution networks to bring our products to over 60 countries worldwide.
We recognize that our employees are at the center of our success, and we take pride in a corporate culture that emphasizes our core values: Influence, Inspire, Innovate, Win, & Grow!
Our employees come from a wide range of retail backgrounds, each bringing their own unique skills and talents to the table as we work together to continue our incredible growth. If you are interested in partaking in the journey of building a nationally recognized and leading brand, we want to hear from you!
Why join us?
Benefits & Compensation: Additional details about compensation and benefits eligibility for this role will be provided during the hiring process. All employees are provided competitive compensation, paid training, and employee discounts on our products and services. We offer a range of benefits packages based on employee eligibility, including:
Paid Vacation Time, Paid Sick Leave, Paid Holidays, Parental Leave. Health, Dental, and Vision Insurance. Employee Assistance Program. 401k with generous employer match. Life Insurance.
Job Details
Data Scientist Why this role matters You’ll architect, build, and operate the data infrastructure that powers analytics, machine learning, and operational reporting across the organization. This is a hands-on role for a data scientist who thrives at the intersection of engineering, modeling, and production-grade systems.
What you’ll do Design and evolve our lakehouse architecture (Delta Lake on AWS/Azure), including storage layout, compute strategy (Databricks, EMR, Synapse), and performance SLAs Build robust batch and streaming data pipelines using Apache Spark (PySpark/Scala), Databricks Workflows, Azure Data Factory, and event-driven integrations (Kinesis, Event Hubs, Kafka) Develop and maintain analytical and ML-ready data models, semantic layers, and dimensional schemas for BI and production use Implement observability and reliability features including custom Spark metrics, anomaly detection, logging, and automated data quality checks Optimize compute and storage performance through cluster tuning, caching, partitioning, and format selection, with measurable cost savings Enforce data governance policies including RBAC, row-level security, cataloging, lineage tracking, and compliance with GDPR, HIPAA/FHIR, and CCPA/CDPA Collaborate with analytics, product, and platform teams to define SLAs, manage incident response, and guide data contract best practices Mentor junior engineers and lead design reviews, setting standards for scalable, maintainable data systems
What you bring 8+ years of experience in data science or data engineering Expert-level Python and SQL; working knowledge of Scala/Java for Spark 3–5+ years of experience with Apache Spark and Databricks (including Delta Live Tables and performance tuning) Strong cloud experience in AWS (S3, EMR, Glue, Lambda, Kinesis) and/or Azure (ADLS Gen2, ADF, Event Hubs, Synapse) Experience with orchestration tools (Airflow, ADF) and transformation frameworks (dbt) Familiarity with data warehouses such as Snowflake, Redshift, or Databricks SQL Proven track record of cost and performance optimization in cloud data environments Solid foundation in data modeling, CI/CD, Docker/Linux, and Git Ability to translate business needs into scalable data products and lead projects end-to-end
Nice to have Experience with custom Spark listeners, low-latency streaming, or event-driven architectures Exposure to healthcare data pipelines (FHIR) and DLT troubleshooting Dashboarding experience with Power BI, Tableau, or Looker Familiarity with governance frameworks and MLOps (feature stores, model monitoring)
Our stack Databricks, Spark (PySpark/Scala), Delta Lake, Airflow, ADF, dbt, AWS (S3/EMR/Glue/Kinesis), Azure (ADLS/Synapse/Event Hubs), Terraform, GitHub Actions, Docker, CloudWatch, REST
Success in 6–12 months looks like Reliable, observable pipelines with
Read on to fully understand what this job requires in terms of skills and experience If you are a good match, make an application.
This Jobot Job is hosted by: Kendall Kaing Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume. Salary: $80,000 - $130,000 per year
A bit about us:
Are you interested in working for the world's largest cannabis market with a footprint that covers the entire breadth of the state of California? Are you someone who wants to be part of the growth of a fast-growing industry? At client company, our mission is clear: to provide the ultimate one stop shop cannabis experience by offering exceptional customer service and diversified products. We strive to build long-term customer loyalty. We’re building a consumer-centric organization that is focused on sharing the transformational potential of cannabis with the world.
Our product line is one of the best-selling cannabis brands in the market today and has claimed the title of the best-selling vape brand across all BDSA-tracked markets and best-selling brand overall in the California market! We are rooted in California and have expanded our operations across the United States, with even more growth on the horizon! Additionally, we’re building distribution networks to bring our products to over 60 countries worldwide.
We recognize that our employees are at the center of our success, and we take pride in a corporate culture that emphasizes our core values: Influence, Inspire, Innovate, Win, & Grow!
Our employees come from a wide range of retail backgrounds, each bringing their own unique skills and talents to the table as we work together to continue our incredible growth. If you are interested in partaking in the journey of building a nationally recognized and leading brand, we want to hear from you!
Why join us?
Benefits & Compensation: Additional details about compensation and benefits eligibility for this role will be provided during the hiring process. All employees are provided competitive compensation, paid training, and employee discounts on our products and services. We offer a range of benefits packages based on employee eligibility, including:
Paid Vacation Time, Paid Sick Leave, Paid Holidays, Parental Leave. Health, Dental, and Vision Insurance. Employee Assistance Program. 401k with generous employer match. Life Insurance.
Job Details
Data Scientist Why this role matters You’ll architect, build, and operate the data infrastructure that powers analytics, machine learning, and operational reporting across the organization. This is a hands-on role for a data scientist who thrives at the intersection of engineering, modeling, and production-grade systems.
What you’ll do Design and evolve our lakehouse architecture (Delta Lake on AWS/Azure), including storage layout, compute strategy (Databricks, EMR, Synapse), and performance SLAs Build robust batch and streaming data pipelines using Apache Spark (PySpark/Scala), Databricks Workflows, Azure Data Factory, and event-driven integrations (Kinesis, Event Hubs, Kafka) Develop and maintain analytical and ML-ready data models, semantic layers, and dimensional schemas for BI and production use Implement observability and reliability features including custom Spark metrics, anomaly detection, logging, and automated data quality checks Optimize compute and storage performance through cluster tuning, caching, partitioning, and format selection, with measurable cost savings Enforce data governance policies including RBAC, row-level security, cataloging, lineage tracking, and compliance with GDPR, HIPAA/FHIR, and CCPA/CDPA Collaborate with analytics, product, and platform teams to define SLAs, manage incident response, and guide data contract best practices Mentor junior engineers and lead design reviews, setting standards for scalable, maintainable data systems
What you bring 8+ years of experience in data science or data engineering Expert-level Python and SQL; working knowledge of Scala/Java for Spark 3–5+ years of experience with Apache Spark and Databricks (including Delta Live Tables and performance tuning) Strong cloud experience in AWS (S3, EMR, Glue, Lambda, Kinesis) and/or Azure (ADLS Gen2, ADF, Event Hubs, Synapse) Experience with orchestration tools (Airflow, ADF) and transformation frameworks (dbt) Familiarity with data warehouses such as Snowflake, Redshift, or Databricks SQL Proven track record of cost and performance optimization in cloud data environments Solid foundation in data modeling, CI/CD, Docker/Linux, and Git Ability to translate business needs into scalable data products and lead projects end-to-end
Nice to have Experience with custom Spark listeners, low-latency streaming, or event-driven architectures Exposure to healthcare data pipelines (FHIR) and DLT troubleshooting Dashboarding experience with Power BI, Tableau, or Looker Familiarity with governance frameworks and MLOps (feature stores, model monitoring)
Our stack Databricks, Spark (PySpark/Scala), Delta Lake, Airflow, ADF, dbt, AWS (S3/EMR/Glue/Kinesis), Azure (ADLS/Synapse/Event Hubs), Terraform, GitHub Actions, Docker, CloudWatch, REST
Success in 6–12 months looks like Reliable, observable pipelines with