Genentech
Sr. Measurement & Optimization Engineer
Genentech, San Francisco, California, United States, 94199
The Position
The Senior ML Engineer sits on the Data Science Team within our Strategic Analytics & Intelligence Organization (SAI) and exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively. As a center of excellence, the Commercial Data Science team uses advanced data science capabilities, working across CMG to develop strategic and holistic solutions by identifying and leading innovative analytic projects & pilots to enable patient and customer solutions.The Opportunity
We are looking for a Sr. Measurement & Optimization Engineer with solid expertise in Statistical and Machine Learning (ML) modeling for Measurement and Optimization. The ideal candidate is someone who has significant hands-on experience developing production-grade predictive models and algorithms, and can also communicate technical findings and recommendations effectively to business teams.The Senior Engineer will manage and guide data science and data engineering elements of AI/ML projects.You will drive the development, deployment and industrialization of enterprise applications using advanced Statistical, Econometric, and Non-parametric modeling techniques to quantify the impact of promotional and non-promotional activities and generate recommendations for improvement.Develop a deep understanding of customers and market dynamics, and apply your technical skills to advance that knowledge and guide the organization, delivering products that help create an integrated customer experience for customers.Help partners define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide.Apply ML and Statistics based approaches to answer a variety of complex business questions using multiple data sources and technical tools.Act as subject matter expert for applicable data science and other advanced analytical methodologies, programs, and projects, particularly in the areas of statistical modeling, A/B testing, experimental design, and time-series analysis.Collaborate within cross-functional teams to develop efficient machine learning based applications, gain alignment and deliver impactful business insights; engage necessary partners to enable better decision-making.Who You Are
You have a BS, MS, or PhD in relevant field: Data Science; Computer Science; Applied Mathematics, Statistics, Economics, Engineering or related field, with a focus on Artificial Intelligence (AI) or Machine Learning (ML).7 years of relevant industry work experience with at least 4 years in Machine Learning, Deep learning, Applied Statistics, Mathematical Optimization, Causal Inference, Bayesian Modeling, and Forecasting with transferable skills across multiple industries.3+ years of experience in the application of Statistical Modeling techniques to enterprise data, with demonstrated ability to drive tangible results.Demonstrated proficiency in using open source libraries and packages such as Pandas, Numpy, Sklearn, TensorFlow, Keras, PyTorch, statsmodels etc. to solve Enterprise problems.Working knowledge of recent advancements in Econometric and Time-Series modeling and use of open-source libraries like Robyn, LightweightMMM, and Meridian.Solid foundational knowledge in Machine Learning with applications focused on Measurement, Causal Inference, and Experimentation.Experience working with large, complex data using Hadoop or Spark or any other big data platforms.Proficiency with industry-standard programming languages such as R or Python.Experience with other data science and cloud-computing tools and platforms (AWS, GCP, etc.).Strong knowledge of secondary data sources including syndicated sales, promotional & marketing data, longitudinal patient level data.Proficiency using ML in a variety of contexts such as revenue attribution, optimization, forecasting, classification, clustering etc.Experience with data visualization tools such as tableau, and/or Qlik, and/or data studio etc.The expected salary range for this position based on the primary location of CA is $172,500 - $320,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.BenefitsGenentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
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The Senior ML Engineer sits on the Data Science Team within our Strategic Analytics & Intelligence Organization (SAI) and exists to help the CMG (Commercial, Medical and Government) organization achieve its vision by unlocking value from data quicker and more effectively. As a center of excellence, the Commercial Data Science team uses advanced data science capabilities, working across CMG to develop strategic and holistic solutions by identifying and leading innovative analytic projects & pilots to enable patient and customer solutions.The Opportunity
We are looking for a Sr. Measurement & Optimization Engineer with solid expertise in Statistical and Machine Learning (ML) modeling for Measurement and Optimization. The ideal candidate is someone who has significant hands-on experience developing production-grade predictive models and algorithms, and can also communicate technical findings and recommendations effectively to business teams.The Senior Engineer will manage and guide data science and data engineering elements of AI/ML projects.You will drive the development, deployment and industrialization of enterprise applications using advanced Statistical, Econometric, and Non-parametric modeling techniques to quantify the impact of promotional and non-promotional activities and generate recommendations for improvement.Develop a deep understanding of customers and market dynamics, and apply your technical skills to advance that knowledge and guide the organization, delivering products that help create an integrated customer experience for customers.Help partners define clear, impactful business priorities, and where possible, use their own expertise or existing analysis/research to influence and guide.Apply ML and Statistics based approaches to answer a variety of complex business questions using multiple data sources and technical tools.Act as subject matter expert for applicable data science and other advanced analytical methodologies, programs, and projects, particularly in the areas of statistical modeling, A/B testing, experimental design, and time-series analysis.Collaborate within cross-functional teams to develop efficient machine learning based applications, gain alignment and deliver impactful business insights; engage necessary partners to enable better decision-making.Who You Are
You have a BS, MS, or PhD in relevant field: Data Science; Computer Science; Applied Mathematics, Statistics, Economics, Engineering or related field, with a focus on Artificial Intelligence (AI) or Machine Learning (ML).7 years of relevant industry work experience with at least 4 years in Machine Learning, Deep learning, Applied Statistics, Mathematical Optimization, Causal Inference, Bayesian Modeling, and Forecasting with transferable skills across multiple industries.3+ years of experience in the application of Statistical Modeling techniques to enterprise data, with demonstrated ability to drive tangible results.Demonstrated proficiency in using open source libraries and packages such as Pandas, Numpy, Sklearn, TensorFlow, Keras, PyTorch, statsmodels etc. to solve Enterprise problems.Working knowledge of recent advancements in Econometric and Time-Series modeling and use of open-source libraries like Robyn, LightweightMMM, and Meridian.Solid foundational knowledge in Machine Learning with applications focused on Measurement, Causal Inference, and Experimentation.Experience working with large, complex data using Hadoop or Spark or any other big data platforms.Proficiency with industry-standard programming languages such as R or Python.Experience with other data science and cloud-computing tools and platforms (AWS, GCP, etc.).Strong knowledge of secondary data sources including syndicated sales, promotional & marketing data, longitudinal patient level data.Proficiency using ML in a variety of contexts such as revenue attribution, optimization, forecasting, classification, clustering etc.Experience with data visualization tools such as tableau, and/or Qlik, and/or data studio etc.The expected salary range for this position based on the primary location of CA is $172,500 - $320,300. Actual pay will be determined based on experience, qualifications, geographic location, and other job-related factors permitted by law. A discretionary annual bonus may be available based on individual and Company performance. This position also qualifies for the benefits detailed at the link provided below.BenefitsGenentech is an equal opportunity employer, and we embrace the increasingly diverse world around us. Genentech prohibits unlawful discrimination based on race, color, religion, gender, sexual orientation, gender identity or expression, national origin or ancestry, age, disability, marital status and veteran status.
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