Our client is looking for a Data Scientist for a two-month contract in San Francisco.
The difference you will make:
We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.
A typical day:
-
- Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes.
- Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Airbnb's systems.
- Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Airbnb's marketing initiatives.
- Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts.
- Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies.
- PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience.
- Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark.
- Proficiency in statistical programming (Python and R) and database usage (SQL).
- Experience with media mix modeling (MMM).
- Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
- Proven track record of solving business problems through data science methods.
- Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field.
- Familiarity with Bayesian modeling and its applications in marketing.
- Experience with causal ML modeling.
- Experience in developing end-to-end models for data-driven decision-making.
location: San Francisco, California
job type: Contract
salary: $115 - 120 per hour
work hours: 8am to 5pm
education: Masters
responsibilities:
Our client is looking for a Data Scientist for a two-month contract in San Francisco.
The difference you will make:
We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.
A typical day:
-
- Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes.
- Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Airbnb's systems.
- Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Airbnb's marketing initiatives.
- Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts.
- Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies.
- PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience.
- Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark.
- Proficiency in statistical programming (Python and R) and database usage (SQL).
- Experience with media mix modeling (MMM).
- Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
- Proven track record of solving business problems through data science methods.
- Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field.
- Familiarity with Bayesian modeling and its applications in marketing.
- Experience with causal ML modeling.
- Experience in developing end-to-end models for data-driven decision-making.
qualifications:
Our client is looking for a Data Scientist for a two-month contract in San Francisco.
The difference you will make:
We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.
A typical day:
-
- Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes.
- Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Airbnb's systems.
- Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Airbnb's marketing initiatives.
- Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts.
- Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies.
- PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience.
- Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark.
- Proficiency in statistical programming (Python and R) and database usage (SQL).
- Experience with media mix modeling (MMM).
- Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
- Proven track record of solving business problems through data science methods.
- Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field.
- Familiarity with Bayesian modeling and its applications in marketing.
- Experience with causal ML modeling.
- Experience in developing end-to-end models for data-driven decision-making.
skills: Our client is looking for a Data Scientist for a two-month contract in San Francisco.
The difference you will make:
We are seeking an experienced Data Scientist with deep expertise and experience building data pipelines and automating measurement systems. The ideal candidate will have experience working with Apache Airflow and Spark, as well as a comprehensive understanding of SQL. They are expected to be fluent in multiple statistical programming languages, particularly R and Python. They should also be familiar with causal inference methodologies, including experimental and observational approaches. The ideal candidate will be capable of hands-on data work to produce insights and recommendations for stakeholders, driving impactful decisions in our marketing efforts.
A typical day:
-
- Data Pipelines: Build novel data pipelines that accelerate the work of our data science team, including automating data validation, unit testing, and other common processes.
- Productionalizing Prototypes: Refine prototypes built by other scientists and prepare them to be productionalized within Airbnb's systems.
- Causal Inference: Apply and develop causal inference methods, especially around MMM, to estimate the effectiveness of Airbnb's marketing initiatives.
- Data Analysis: Conduct data pulls, analyze trends, and create new features to support measurement efforts.
- Collaboration: Work effectively with cross-functional teams, providing insights that optimize marketing strategies.
- PhD in Economics, Statistics, Marketing, or a related field, or a Masters Degree in a similar field with 2+ years of experience.
- Deep knowledge of data management tools, systems, and processes, including Apache Airflow and Spark.
- Proficiency in statistical programming (Python and R) and database usage (SQL).
- Experience with media mix modeling (MMM).
- Ability to communicate complex concepts clearly to stakeholders at varying technical levels.
- Proven track record of solving business problems through data science methods.
- Passion for marketing and consumer science, with a desire to stay informed about the latest advances in the field.
- Familiarity with Bayesian modeling and its applications in marketing.
- Experience with causal ML modeling.
- Experience in developing end-to-end models for data-driven decision-making.
Equal Opportunity Employer: Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.
At Randstad Digital, we welcome people of all abilities and want to ensure that our hiring and interview process meets the needs of all applicants. If you require a reasonable accommodation to make your application or interview experience a great one, please contact HRsupport@randstadusa.com.
Pay offered to a successful candidate will be based on several factors including the candidate's education, work experience, work location, specific job duties, certifications, etc. In addition, Randstad Digital offers a comprehensive benefits package, including health, an incentive and recognition program, and 401K contribution (all benefits are based on eligibility).
This posting is open for thirty (30) days.
Qualified applicants in San Francisco with criminal histories will be considered for employment in accordance with the San Francisco Fair Chance Ordinance.
Qualified applicants in the unincorporated areas of Los Angeles County with criminal histories will be considered for employment in accordance with the Los Angeles County's Fair Chance Ordinance for Employers.
We will consider for employment all qualified Applicants, including those with criminal histories, in a manner consistent with the requirements of applicable state and local laws, including the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance.
