AI Machine Learning Senior Vice President

Job Opportunity At AlixPartners

At AlixPartners, we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve. We prize diversity and inclusion, the intellectually curious, the inventive, and the forward-thinking. We invite you to influence the way we work and define the way we embrace tomorrow. By understanding, respecting, and honoring the needs of our employees, clients, and communities, AlixPartners actively promotes an inclusive environment. We strongly believe in the value that diversity brings to our experiences and are committed to the perpetual enhancements of initiatives, policies, and practices. We hold ourselves accountable by providing the space for authenticity, growth, and equity for everyone. AlixPartners has embraced a hybrid work model to provide flexibility and support our employees' work-life integration. Our hybrid model combines a mix of in-person (at client site or AlixPartners office) and remote working. Travel is part of this position, but the frequency may vary based on client, team, and individual circumstances. Are you passionate about a future that exceeds your expectations? Here, at AlixPartners your passion becomes your career. We work in smaller and more senior teams that bring deep industry and functional knowledge to our clients. If you join our practice, you will work with financially secure, under-performing and distressed companies across a variety of urgent, high impact situations. Our elite professionals are recognized experts in their respective fields, bringing to bear their skills and experience to craft measurable, improved outcomes for our clients. In this role, you will have the chance to create ETL workflows, scripts, statistical models, and visualizations while taking responsibility for the design, build, test, execution, and support of the data migration, cleansing, wrangling, etc. The ideal candidate will have a detailed understanding of the underlying data and data structures of multiple systems to allow in-depth analysis of existing and potential data insights. Data Modeling

Selecting features, building and optimizing classifiers using machine learning techniques Executing machine learning projects using state-of-the-art methods Extending company's data with third party sources of information when needed Creating automated anomaly detection systems and constant tracking of its performance Data Manipulation

Experience with common data science toolkits, such as Python, PySpark, R Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Collect data from a wide variety of corporate databases, including various SQL databases -Microsoft, Redshift, Teradata, Oracle, Netezza, etc.-, Access, Excel, plain or formatted text files, OLAP cubes -Microsoft, Oracle-, and no-SQL databases Parse data out of poorly structured XML and invalid HTML documents Use regular expressions to extract information from un-structured text documents Deal with missing data through multiple-imputation or the use of advanced models Automate boring tasks with scripts Data Organization

Build effective, reliable, and robust ETL processes that govern the data ingestion flow Design database models, consistent table structures, and advanced dimensional schemas that carry out data quality and consistency standards Apply modeling approaches, business intelligence patterns, and data management techniques Understanding of cloud architectures. Some knowledge in Azure, AWS or GCP is desired Data Analysis

Demonstrate advanced SQL skills, such as CTEs and window functions, to work with extensive amounts of data at various aggregation levels Review and analyze legacy code/