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Postdoctoral researcher on causal inference for monitoring machine learning algorithms
UCSF
After a machine learning (ML)-based system is deployed, monitoring its performance is important to ensure the safety and effectiveness of the algorithm over time. When an ML algorithm interacts with its environment, the algorithm can affect the data-generating mechanism and be a major source of bias when evaluating its standalone performance, an issue known as performativity. Although prior work has shown how to validate models in the presence of performativity using causal inference techniques, there has been little work on how to monitor models in the presence of performativity. The goal of this project is to bring together techniques from causal inference and statistical process control to develop a comprehensive framework for post-market monitoring of ML algorithms.

We are seeking a postdoctoral researcher to join our lab. The primary responsibilities are:

Develop new statistical methods/frameworks for post-market monitoring of ML algorithms
Implement a software package that can be readily used by ML developers, health AI deployment teams, and ML auditors/regulators
Write, edit, and publish research manuscripts in collaboration with the team

Our team is highly collaborative and includes members with wide-ranging expertise:

Jean Feng: PI of the lab. Primary advisor of postdoctoral researcher. Assistant Professor in the Department of Epidemiology and Biostatistics at UCSF.
Fan Xia: Co-advisor of postdoctoral researcher. Assistant Professor in the Department of Epidemiology and Biostatistics at UCSF.
Alexej Gossmann: Staff Fellow and mathematical statistician in the Division of Imaging, Diagnostics, and Software Reliability (CDRH/OSEL/DIDSR) at the FDA.

We are looking to hire a postdoctoral researcher to join the team. The position (100% funded) will be for two years. Salary and benefits are competitive.

For details on qualifications and application, please see the link.
Link: https://www.jeanfeng.com/joining.html#postdoctoral-researcher-on-causal-inference-for-monitoring-machine-learning-algorithms
Sr. Data Analytics Developer
Mathematica
Mathematica is seeking an intellectually curious Sr. Data Analytics Developer in any of our locations who is passionate about using big data to answer research questions that influence decision making in U.S. health care policy. The ideal candidate will work in languages such as Python and SQL, or statistical programming languages. Individuals with an interest in confronting the challenges of working with large, complex data sets, an interest in data manipulation and analysis, and a desire to become a subject matter expert in health care data are strongly encouraged to apply.
Link: https://careers.mathematica.org/job/washington/sr-data-analytics-developer-remote-eligible-health-division/727/63423671680
Data Analytics Developer
Mathematica
Mathematica is seeking an intellectually curious Data Analytics Developer in any of our locations who is passionate about using big data to answer research questions that influence decision making in U.S. health care policy. The ideal candidate will work in languages such as Python and SQL. Individuals with an interest in confronting the challenges of working with large, complex data sets, an interest in data manipulation and analysis, and a desire to become a subject matter expert in health care data are strongly encouraged to apply.
Link: https://careers.mathematica.org/job/washington/data-analytics-developer-remote-eligible-health-division/727/63423671664
Statistical Analyst
Mathematica
Mathematica is looking for masters-level health Statistical Analysts to join our vibrant group of over 50 statisticians and data scientists. The contributions of our statisticians and statistical analysts underpin our ability to produce crucial evidence for policy and decision makers, ultimately furthering our mission to improve public well-being. For example, our statistical analysts have developed COVID-19 decision tools, extended state-of-the-art methods for identifying treatment effect heterogeneity to enhance primary care delivery, and leveraged Bayesian factorial design to improve the presentation of school choice information to low-income parents. As part of their employment, statistical analysts benefit from the mentorship of more senior statisticians and subject-matter experts, learning new techniques and familiarizing themselves with new topic areas through involvement in analyses.
Link: https://careers.mathematica.org/job/washington/statistical-analyst-remote-eligible-health-division/727/65188972192
Principal Economist (L7), Amazon Marketing Science & Tech
Amazon.con
Amazon’s Global Fixed Marketing Campaign Measurement & Optimization (CMO) team is looking for a senior economic expert in causal inference and applied ML to advance the economic measurement, accuracy validation and optimization methodologies of Amazon’s global multi-billion dollar fixed marketing spend. This is a thought leadership position to help set the long-term vision, drive methods innovation, and influence cross-org methods alignment. This role is also an expert in modeling and measuring marketing and customer value with proven capacity to innovate, scale measurement, and mentor talent.

This candidate will also work closely with senior Fixed Marketing tech, product, finance and business leadership to devise science roadmaps for innovation and simplification, and adoption of insights to influence important resource allocation, fixed marketing spend and prioritization decisions. Excellent communication skills (verbal and written) are required to ensure success of this collaboration. The candidate must be passionate about advancing science for business and customer impact.
Link: https://www.amazon.jobs/en/jobs/2545546/principal-economist-fixed-marketing-campaign-measurement-optimization-cmo
Sr. Economist (L6), Amazon, Marketing Science and Tech
Amazon.com
The Campaign Measurement & Optimization (CMO) organization is looking for a Senior Economist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge causal inference models using ML. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement at Amazon and its subsidiaries.

Link: https://www.amazon.jobs/en/jobs/2597967/senior-economist-campaign-measurement-optimization-cmo
Data Scientist -Ads
Netflix
At Netflix, the Ads Data Science and Engineering team plays a crucial role in establishing the foundation of our ads business. Our mission encompasses conducting comprehensive analyses, developing analytic tools, and creating predictive models using machine learning, all with the overarching goal of enhancing choices and joy for our members. As a leader in this domain, you’ll collaborate closely with partner teams to strategize on overarching business goals. Your team will be at the forefront of developing and implementing advanced optimization algorithms and machine learning models, driving significant enhancements to our advertising systems. With a commitment to analytical rigor, your team will evaluate ideas, dissect problems, build workflows, provide recommendations, and lead end-to-end analytics initiatives in this transformative space.

Please directly apply through the link, if interested
Link: https://jobs.netflix.com/jobs/318059384
Senior Data Scientist (L5), Games
Netflix
Data Science and Engineering (‘DSE’) at Netflix is aimed at using data, analytics, and sciences to improve various aspects of our business. We are looking for a Senior Data Scientist to join our Games DSE team, leading experimentation and advanced data science needs. This role will be partnering closely with our Game studio stakeholders to drive data informed decisions by building predictive models, conducting statistical analysis and deriving business insights. As a member of this team, you will also play a critical role in presenting insights that shape our decision making and ensure decisions are sound from a statistical perspective.

What You Will Do:

Partner with our Game stakeholders (e.g., Netflix Games Development team, Game Developers, Game Strategy, Planning & Analysis team) on advanced analytic initiatives (e.g., prediction modeling, causal inference, experimentation etc)
Lead the design, analysis, and interpretation of experiments that shape decision-making around Games at Netflix
Proactively perform data exploration to discover innovation and testing opportunities
Drive and implement high impact projects end to end
Present your research and insights to key stakeholders
Work with business stakeholders to connect analysis to key decisions that affect the business to influence and drive impact to the business
Balance handling ad hoc requests while also driving larger projects forward

Please directly apply through the link, if interested
Link: https://jobs.netflix.com/jobs/321386898
Applied Scientist II, Customer Behavior Analytics
Amazon
Are you seeking an environment where you can drive innovation? Do you want to apply learning techniques and advanced mathematical modeling to solve real world problems? Do you want to play a key role in the future of Amazon’s Retail business? This job for you! The Customer Behavior Analytics (CBA) team is looking for motivated individuals with strong ML and analytical skills. The CBA team is responsible for the architecture, design and implementation of tools used to understand customer behavior, estimate the Economic value of Amazon programs like Prime, and guide program teams on prioritization/investment/policy optimization decisions. Come and join us!

Amazon’s CBA team is looking for Applied Scientists, who can work at the intersection of machine learning, statistics and economics; and leverage the power of big data to solve complex problems like long-term causal effect estimation.
Link: https://www.amazon.jobs/en/jobs/2591201/applied-scientist-ii-dsi
Principal Applied Scientist (L7), Amazon.com, Customer Behavior Analytics
Amazon.com
We’re looking for a Principal Research Scientist interested in solving one of the most challenging business problems in marketing measurement, a thought leader with deep expertise in modeling, and scaling measurement science. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine marketing measurement at Amazon and its subsidiaries.

This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a lead research scientist in the team, you will be responsible for designing and developing cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, developing Deep Learning models for estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces. Unlike many companies who buy existing off-the-shelf marketing measurement systems, we are responsible for studying, designing, and building systems to serve Amazon’s suite of businesses. Our team members have an opportunity to be on the forefront of marketing measurement thought leadership by working on some of the most difficult problems in the industry with some of the best product managers, research scientists, economists and software developers in the business.
Link: https://www.amazon.jobs/en/jobs/2550911/principal-applied-scientist-campaign-measurement-optimization
Sr Applied Scientist (L6), Amazon
Amazon.com
Amazon’s Campaign Measurement & Optimization (CMO) organization is looking for a Senior Applied Scientist interested in solving one of the most challenging business problems in marketing measurement and developing cutting-edge ML model. Working with our team of data scientists, applied scientists, research scientists, and economists, this leader will help redefine scalable marketing measurement at Amazon and its subsidiaries.

This is a high-impact role with opportunities to develop systems and analyze marketing effectiveness that contributes billions of dollars to the business. As a senior scientist, you will be responsible for leading the design and development of the cutting edge measurement and optimization models, while collaborating with businesses, marketers, and software teams to solve key challenges facing the teams. Such challenges include measuring the incremental impact of multi-channel marketing portfolios, estimating the impact on sparse customer actions, and scaling measurement solutions for WW marketplaces.
Link: https://www.amazon.jobs/en/jobs/2596749/senior-applied-scientist-cmo-science
Director, Center for Biostatistics and Data Science (CBDS) within the Institute for Informatics, Data Science and Biostatistics (I2DB)
Washington University School of Medicine in St. Louis
The Institute for Informatics, Data Science, and Biostatistics (I2DB, https://i2db.wustl.edu/) seeks a highly qualified applicant to lead the Center for Biostatistics and Data Science (CBDS). The ideal candidate will be an accomplished mid-career or senior researcher with a track record of extramural funding, teaching excellence, and administrative acumen. The Director of CBDS will serve as a member of the leadership team of I2DB and will oversee research, teaching, and service activities conducted by the CBDS. In addition, the Director of CBDS will serve as a school-wide and university-wide advocate and change agent to advance the frontiers of biostatistics and biomedical data science, particularly where those fields directly impact research, care delivery, or public health. Finally, building on existing scholarly excellence in biostatistics and data science, we anticipate substantial growth of the CBDS in the near and longer term. Therefore, the Director of CBDS will be responsible for establishing and managing a strategic plan to recruit new faculty, develop existing faculty, and expand research, education, and service initiatives.

Specific areas of scholarly emphasis for this opportunity include but are not limited to:

Study design and analytics in support of clinical, epidemiological, and genetic research that focuses on disorders with considerable clinical or public health importance
Data coordination and management in the context of collaborative or multi-center research programs, including both domestic and global health initiatives
The interrogation and understanding of complex administrative and population-level data resources
The reproducible and rigorous application of machine learning and AI-related techniques to enable hypothesis generation and testing in multi-scale and multi-modal data sets
The use of data visualization and interactive computing techniques to better engage humans in the analysis and understanding of biomedical data analytics

Link: https://facultyopportunities.wustl.edu/Posting/Detail/1010996
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