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Senior Data Scientist
Confirmed live in the last 24 hours
Restaurant365

1,001-5,000 employees

Consumer Software
Data & Analytics

Company Stage

Private

Total Funding

$262.5M

Founded

2011

Headquarters

Irvine, California

Growth & Insights
Headcount

6 month growth

27%

1 year growth

109%

2 year growth

459%
Locations
Remote
Experience Level
Entry
Junior
Mid
Senior
Expert
Desired Skills
Agile
BigQuery
Data Analysis
Data Science
Google Cloud Platform
Airflow
Keras
Microsoft Azure
NumPy
Pandas
Redshift
Snowflake
SQL
Python
CategoriesNew
Data & Analytics
Requirements
  • 5+ years of data science or related experience for the full data science lifecycle across feature engineering, model development and training, model deployment/ML Ops, and model monitoring and governance
  • 1-2 years of SaaS industry experience required and experience building SaaS industry-specific models such as churn and LTV
  • Exemplary analytical and statistical exploratory skills, problem-solving abilities, and knowledge
  • Advanced knowledge of Python, including extensive experience with these libraries: Pandas, NumPy, SciPy, TensorFlow, Sci-Kit Learn, Keras, Matplotlib, Math
  • Advanced knowledge of SQL
  • ML Ops platform experience; preferred experience specifically with Google Cloud Platform (GCP) across Vertex AI, BigQuery, Google Cloud Storage, and Document AI
  • Familiarity with a Modern Data Stack (I.e. ETL tools like dbt, Airflow, Fivetran and cloud data warehouses like BigQuery, Snowflake, Azure, or Redshift)
  • Excellent communication and collaboration skills, with the ability to influence stakeholders at all levels of the organization
  • Strong attention to detail and excellent written/verbal communication skills
  • Restaurant industry experience preferred
Responsibilities
  • Work closely with cross-functional teams and executives to proactively identify high impact opportunities to increase revenue or reduce costs for Restaurant 365 and its customers using data science and machine learning tools and techniques
  • Execute on data science initiatives through all phases from data cleaning and exploration, feature engineering, model selection, hyperparameter tuning, model deployment, model documentation and governance, and model maintenance and monitoring
  • Communicate results and partner with cross-functional teams to develop and implement strategies to improve business results (e.g., when developing a churn model, work with Customer Success to take action on highly impactful features to the model that would result in a reduction in churn)
  • Work with Business Intelligence & Analytics to monitor the success of recommendations and further refine recommendations, strategy, and the model going forward
  • Proactively identify data ingestion needs and provide requirements to Data Engineering
  • As the first data science hire, be a thought leader and game-changer for R365. That said, you will have support from your manager and others with data science backgrounds, plus world-class data science technology with Google Cloud Platform
  • Participate in an Agile scrum team
  • Mentor and train members of the team in data science and machine learning techniques to elevate the overall advanced analytics capabilities of the Data & Analytics team
  • Work closely with business intelligence analysts and data engineering
  • While the nature of data science is experimental, exploratory, creative, and innovative, balance that and prioritize value for your customer with the results of the models. This is a very practical implementation role, not a pure research role
  • Clean data, QA your own work, review your teammates', and pair program with other members of the team
  • Create documentation for reference, process, and results for relevant data analyses, data products, and data infrastructure
  • Stay up to date with industry trends and emerging technologies in data science and AI, and evaluate their potential impact on the business
  • Other duties as assigned