Data Scientist

Data Scientist Location:

Remote within 100 miles of

Culver City, CA Duration:

12 months

Schedule :

40 hours

Pay:

$62-$64.24 DOE The Planet Group is looking for a Data Scientist to join our well-known Fortune 500 client on a 12-month contract, working in a remote schedule from Culver City, CA. Data Scientist |

Qualifications:

Bachelor's degree and 3 years of experience in Data Science field, or a Master's degree in Data Science, Computer Science, or a related field with 2 years of experience. Strong foundation in probability and statistics. Proficiency in SQL and Python or R to work with large data sets. Knowledge around supervised and unsupervised machine learning algorithms (regression, classification, clustering, decision trees, neural networks, etc). Understands digital marketing data and KPIs - Social, SEO, Paid Media, etc. Ability to both solve problems with an analytical mind set and explain findings and methodologies to technical and creative teams. Looking for someone with 3-5 years of experience manipulating data sets and using statistical /ML models to extract insights and visualize them for stakeholders. Ability to read and analyze large amount of content in Simplified Chinese. Experience in applying causal inference for marketing, and familiar with marketing mix modeling or multi-touch attribution models. Knowledge of model evaluation frameworks including metric definition, sampling strategy, and human-in-the-loop processes. Proficiency in code collaboration/version control systems (git/github/gitlab). Data Scientist |

Description:

Build and maintain data driven optimization models, experiments, forecasting algorithms and machine learning models to better campaign performance, identifying trends and optimize strategy. Provide causal analysis to evaluate impact from various marketing initiatives, including both organic and paid ad placements. Design and continuously improve models that measure upper funnel marketing impact, integrating multiple metrics and a diverse source of data in both structured and unstructured format. Collaborate with cross-functional teams and propose solutions to address business problems. Assess business needs to translate model outputs into tangible and actionable findings and reports for both marketing and product.