Zenith
Data Scientist
Zenith, San Luis Obispo, California, us, 93403
Job Description
What does Zenith Data Sciences do... Working closely with both the Business Planning and Analytics teams, Data Sciences designs and implements statistical models and machine learning solutions that tie our clients’ marketing to real-world business goals. We use these models to understand past performance, predict future performance, and inform and optimize future decisions. Our work brings our clients closer to their marketing, helping them understand if they are talking to the right people in the right way. What does a successful Data Scientist look like?
We don’t all look the same, and we don’t expect you to, either. But a successful Data Scientist should share our passion for emerging tech and media, bring an evidence-based approach to decision-making, determine a point of view and share it in a positive way, gear up for a challenge, and always crave to learn more and improve. We are looking for prior experience in marketing analytics, especially digital creative and media, but this isn’t necessarily a requirement. At least 1-2 years of prior professional experience is highly desired. What does a Data Scientist do day-to-day?
Data Scientists form the foundation of the Data Sciences team, structuring and analyzing data, implementing and interpreting models that feed business-improving insights, and putting it all together into presentations that bring the story to life for our clients. Data Scientists work closely with the Data Science Manager to help execute the broader vision for their account, and to continually evolve our Data Science solutions. Design, estimate, tune, score and maintain advanced statistical and mathematical models (e.g. classification, numeric forecasts, customer segmentation, customer propensity, attribution, etc.). Produce accurate statistical analysis and ensure high quality of the data analysis produced. Interpret, document and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations. Take analytical objectives and define data requirements. Extract, clean, and transform both customer level, and aggregated data for analysis, modelling, segmentation and reporting. Qualifications
BS/MS degree in quantitative field (mathematics, physical science, engineering, statistics, economics). 2+ years business experience working on data science projects. Strong understanding of mathematical modeling, probability, and statistics including linear/logistic regression, decision trees, and optimization modelling. Experience with developing and applying advanced statistical methods to analytical problems including analysis of time series. Proficient with Python/R/SAS/SPSS for statistical modeling and machine learning. Familiarity with Relational Databases and SQL programming. Familiar with data processing and management support tools such as MS Office, advanced excel analysis, Power BI, Tableau. Strong written and verbal presentation skills. Proactive, collaborative, adaptable, willing to expand technical and business skills. Benefits
Compensation Range: $70,000 - $105,000 annually. This is the pay range the Company believes it will pay for this position at the time of this posting. For this role, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. All your information will be kept confidential according to EEO guidelines. The Company anticipates the application window for this job posting will end 3/5/2024.
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What does Zenith Data Sciences do... Working closely with both the Business Planning and Analytics teams, Data Sciences designs and implements statistical models and machine learning solutions that tie our clients’ marketing to real-world business goals. We use these models to understand past performance, predict future performance, and inform and optimize future decisions. Our work brings our clients closer to their marketing, helping them understand if they are talking to the right people in the right way. What does a successful Data Scientist look like?
We don’t all look the same, and we don’t expect you to, either. But a successful Data Scientist should share our passion for emerging tech and media, bring an evidence-based approach to decision-making, determine a point of view and share it in a positive way, gear up for a challenge, and always crave to learn more and improve. We are looking for prior experience in marketing analytics, especially digital creative and media, but this isn’t necessarily a requirement. At least 1-2 years of prior professional experience is highly desired. What does a Data Scientist do day-to-day?
Data Scientists form the foundation of the Data Sciences team, structuring and analyzing data, implementing and interpreting models that feed business-improving insights, and putting it all together into presentations that bring the story to life for our clients. Data Scientists work closely with the Data Science Manager to help execute the broader vision for their account, and to continually evolve our Data Science solutions. Design, estimate, tune, score and maintain advanced statistical and mathematical models (e.g. classification, numeric forecasts, customer segmentation, customer propensity, attribution, etc.). Produce accurate statistical analysis and ensure high quality of the data analysis produced. Interpret, document and present/communicate analytical results to multiple business disciplines, providing conclusions and recommendations. Take analytical objectives and define data requirements. Extract, clean, and transform both customer level, and aggregated data for analysis, modelling, segmentation and reporting. Qualifications
BS/MS degree in quantitative field (mathematics, physical science, engineering, statistics, economics). 2+ years business experience working on data science projects. Strong understanding of mathematical modeling, probability, and statistics including linear/logistic regression, decision trees, and optimization modelling. Experience with developing and applying advanced statistical methods to analytical problems including analysis of time series. Proficient with Python/R/SAS/SPSS for statistical modeling and machine learning. Familiarity with Relational Databases and SQL programming. Familiar with data processing and management support tools such as MS Office, advanced excel analysis, Power BI, Tableau. Strong written and verbal presentation skills. Proactive, collaborative, adaptable, willing to expand technical and business skills. Benefits
Compensation Range: $70,000 - $105,000 annually. This is the pay range the Company believes it will pay for this position at the time of this posting. For this role, the Company will offer medical coverage, dental, vision, disability, 401k, and paid time off. All your information will be kept confidential according to EEO guidelines. The Company anticipates the application window for this job posting will end 3/5/2024.
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