Data Scientist III- #26-18366

US Tech Solutions; Princeton (NJ); On-site; USD 229,233,000 - 249,290,000; Full time

Job summary

US Tech Solutions seeks a Data Scientist for measurement and attribution in Princeton, NJ, on a contract basis. You will use data science techniques to analyze marketing activities, estimate growth, and work on MMM/Marketing Mix Modeling and disaggregate event-stream data.

You will build and revise code, engage in hands-on analytics, and collaborate with vendors to ensure data quality, while promoting innovative analytics and model diagnostics.

Qualifications

• Measurement of digital and offline measurement, including attribution, MMM, and linear TV impact.
• Proficiency in SQL, Python and/or R or other statistical programming language.
• Experience working with and measuring offline (such as Salesforce), TV, digital media, and CRM data.
• Knowledge of statistics/data science, including regression, hierarchical or mixed regression, and machine learning techniques (Naïve Bayes, Markov Chain, Random Forest etc.).
• Advanced modeling skills with Python and R.
• Cloud environment experience, especially Snowflake.
• Experience working with platforms like Dataiku/Databricks.
• Understanding of marketing goals and how different media channels support these goals.
• Preference, experience in pharma/life sciences.

Responsibilities

• Manage data collection and modeling with vendors.
• Develop reports and processes to ensure data quality control.
• Promote innovation in analytics, implement and refine attribution models.
• Interpret and visualize model estimates and diagnostics.
• Champion continuous improvement and strategic evolution.

Skills

SQL

Python

R

Statistics

Machine learning

MMM

Tools

Snowflake

Dataiku

Databricks

Job description

$80-$87 per hour

Princeton, NJ

Contract

Duration:12+ months

Description:

The Data Scientist - Measurement & Attribution tasks include:

You will play an important role in our US-based attribution modeling capabilities. You will use data science techniques to examine marketing activities and to estimate their growth. These projects will include Media Mix Optimization or Marketing Mix Modeling, Analysis of Covariance (test and control), Cluster Analysis, and Attribution Modeling of disaggregate event-stream data. You will be hands-on keyboard building and revise code and inspire creativity.

Expectations:

• Manage data collection and modeling with vendors.
• Develop reports and processes to ensure data quality control.
• Promote innovation in analytics, implement and refine attribution models.
• Interpret and visualize model estimates and diagnostics.
• Champion continuous improvement and strategic evolution.

Experience:

• Measurement of both digital and offline measurement, including attribution, MMM, and linear TV impact.
• Proficiency in SQL, Python and/or R or other statistical programming language.
• Experience working with and measuring offline (such as salesforce), TV, digital media, and CRM data.
• Knowledge of statistics/data science, including regression, hierarchical or mixed regression, and machine learning techniques (Naïve Bayes, Markov Chain, Random Forest etc.).
• Advanced modeling skills with Python and R.
• Cloud environment experience, especially Snowflake.
• Experience working with platforms like Dataiku/Databricks.
• An understanding of marketing goals and how different media channels support these goals.
• Preference, experience in pharma/life sciences.

About US Tech Solutions:

US Tech Solutions is a global staff augmentation firm providing a wide range of talent on-demand and total workforce solutions. To know more about US Tech Solutions, please visit www.ustechsolutions.com .

US Tech Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

AI Statement: By applying, you acknowledge that AI-assisted tools may be used during hiring.

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