Popular Bank · 15 hours ago
Artificial Intelligence Manager II
Charlotte, NC
Full-time
Remote
Senior Level, Lead/Staff
15+ years exp
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Responsibilities
Provide leadership and mentorship to a diverse team of data scientists, analytics specialists, and model operation specialists, promoting a culture of excellence and continuous learning.
Collaborate with business units and stakeholders to understand and analyze complex business problems and use data analytics to propose innovative solutions.
Develop, validate, and maintain advanced predictive and prescriptive models, utilizing machine learning and optimization techniques.
Develop and execute a strategic vision for the Advanced Data Analytics COE and AI initiatives, ensuring alignment with broader organizational goals.
Establish a systematic framework for data analysis, hypothesis testing, and model development.
Drive the design and deployment of real-time data-driven products, ensuring scalability and robustness.
Champion data literacy and foster a data-driven culture within the organization, providing training where necessary.
Establish and monitor key performance indicators to track the success and value delivered by the data science initiatives.
Ensure compliance of analytics and AI initiatives with data governance, privacy, and regulatory requirements.
Promote an agile, collaborative, and innovative environment within the Advanced Data Analytics COE.
Ability to execute a range of analytical concepts and statistical techniques, from hypothesis development and test/experiment design to data analysis, conclusion derivation, and formulating actionable recommendations for business units.
Recognized as the go-to expert in analytics methodologies, upholding standards, and best practices, with a focus on outcomes measurement and study design.
Collaborative mindset, working closely with data science colleagues to pinpoint gaps, enhance quality, and exchange insights on advanced modeling techniques, assets, features, and learnings.
Qualification
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Required
Master’s degree or PhD in Statistics, Mathematics, Data Science, Economics, or a related field.
A minimum of 15 years of experience in customer analytics or decision sciences, with at least 7 years in a leadership role.
Strong proficiency in core Data Science, Machine Learning and Statistical modeling. In-depth experience in techniques from time-series forecasting and/or causal inference.
Experience with Experiment Design, Natural Language Processing, Neural Network architectures, Recommendation Systems, and Large Language Models is highly desirable.
Experience with Graph Networks, Fraud detection, financial crimes implementations.
Experience with analytics tools and programming languages such as R, Python, SAS, and SQL.
Implemented machine learning model by leveraging algorithms such as Linear Regression, Decision tree, SVM, Clustering, Naive Bayes, KNN, Random Forest, PCA, AdaBoost.
Proficiency in machine learning techniques and deep learning algorithms such as Convolutional Neural Networks (CNNs), Long Short-Term Memory Networks (LSTMs), Recurrent Neural Networks (RNNs), Generative Adversarial Networks (GANs), Radial Basis Function Networks (RBFNs), Multilayer Perceptron (MLPs), Self-Organizing Maps (SOMs).
Expertise in validation of AI/ML models using one or more methods such as A/B testing, Chi-Square tests, ANOVA, ANCOVA, MANCOVA, MANOVA, Null Hypothesis, Alternate Hypothesis.
Strong business acumen with the ability to translate data and analytics into actionable business insights and strategies.
Solid understanding of cloud computing environments and experience with deploying models in cloud environments such as AWS, Azure, or GCP.
Marketing cloud, Pega, Adobe analytics, and google analytics.
Experience in leveraging GenAI & LLM capabilities for hyper personalization, enhanced use experience, content generation, translation, and summarization.
Experience in leading data science teams and delivering data capabilities in following waterfall, iterative, scaled agile, scrum, and kanban methodologies.
In-depth knowledge of data integration methodologies such as change data capture, ETL & ELT processes, real-time data processing, micro-services, data lifecycle management, data lake, data warehouse, data vault, data mesh, data marketplace and data science concepts.
Hands-on experience with On-prem & cloud data platforms such as Snowflake, AWS Redshift, Azure Synapse Analytics, Databricks, AWS Aurora, Oracle Exadata, SQL server, Hadoop, Spark, SAS and R.
Excellent data analysis, profiling and statistics skills coupled with proficiency in SQL tools and technologies such as Oracle, SQL Server, MySQL, Pandas, NumPy, Ggplot, Shiny, SciPy, Sci-Kit Learn, and Matplotlib.
Strong proficiency in SQL, Spark, Python, R, SAS or other data manipulation and transformation languages.
Experience of one or more AI/ML platforms in cloud such as Sagemaker, Dataiku, DataRobot, H2O.ai, Snowpark, ModelOp Center, and Domino Data Lab.
Experience in handling high volume of data in structure, semi-structured and unstructured formats such as relational, flat files, XML, JSON, Parquet, Avro, Mainframe copybooks, CSV, Fixed with and hierarchy files.
Excellent communication and presentation skills, with the ability to convey complex analytical concepts to non-technical stakeholders.
Demonstrated experience in leading and developing analytics teams, with a focus on continuous learning and innovation.
In-depth understanding of data governance, data privacy, and regulatory requirements pertaining to customer data.
Experience with DevOps and DataOps products such as Jenkins, Git, GITLab, Maven, Bitbucket, and Jira.
Proficiency in utilizing a range of Machine/Deep Learning algorithms and frameworks, including TensorFlow, PyTorch, scikit-learn, Spark ML, Torch, Huggingface, Keras, Caffe, and CNTK.
Knowledge of big data platforms like Hadoop and Spark is a plus.
Exceptional analytical thinking and problem-solving skills.
Ability to communicate complex data concepts to both technical and non-technical stakeholders effectively.
Strong project management skills with the ability to manage multiple projects simultaneously.
Company
Popular Bank
Popular Bank provides mortgage, cash management, credit cards, loans, investments, financial, and banking services.
1,001-5,000 employees
H1B Sponsorship
Popular Bank has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2023 (1)
2021 (6)
2020 (5)
Funding
Current Stage
Late StageLeadership Team
Yanetsy Iturralde Compain, MSHRM
Our People Strategic Partner, VP - South Florida Region
Meenakshi Thanikachalam
Executive Head of Data & Analytics (Chief Data & Analytics Officer)
Recent News
Wall Street Journal
2023-01-25
Company data provided by crunchbase
