Artificial Intelligence Manager II
Charlotte, NC, US, 28210
Banco Popular
Popular te ofrece la red más extensa de sucursales y cajeros automáticos en Puerto Rico. Conoce nuestros productos y servicios para individuos y negocios.
The Artificial Intelligence Lead plays a pivotal role in spearheading the organization's efforts in harnessing the power of data through advanced analytics, machine learning, and artificial intelligence. This role involves steering the Advanced Data Analytics Center of Excellence (COE), managing model operations specialists, and fostering innovation in data-driven strategies. By closely aligning with business objectives, the Advanced Analytics & AI Lead deploys high-impact solutions that propel decision-making, efficiency, and growth.
Your key responsibilities:
You will collaborate with multifaceted teams of specialists spread across various locations to offer a broad spectrum of data and analytics solutions. You will address complicated challenges and propel advancement within the Enterprise Data & Analytics function.
Specifically:
- 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.
To qualify for the role, you must have:
- 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.
What we look for:
We are seeking enthusiastic and initiative-taking leaders who have a clear vision and an unwavering commitment to remain at the forefront of data technology and science. Our ideal candidates are those who aim to foster team spirit and collaboration and have a knack for adept management. It is essential that you display comprehensive technical proficiency and possess a rich understanding of the industry.
If you have a genuine drive for helping consumers achieve the full potential of their data while working towards your own development, this role is for you.
Region Locations
North Carolina or Puerto Rico
Important: The candidate must provide evidence of academic preparation or courses related to the job posting, if necessary.
ABOUT US
Popular is Puerto Rico’s leading financial institution and have been evolving since it was founded over a century ago. From a small bank it has developed into a large corporation that offer a wide variety of services and financial solutions to our customers, with presence in the United States, the Caribbean and Latin America.
As employees, we are dedicated to making our customers dreams come true by offering financial solutions in each stage of their life. Our extensive trajectory demonstrates the resiliency and determination of our employees to innovate, reach for the right solutions and strongly support the communities we serve; therefore, we value their diverse skills, experiences and backgrounds.
We reaffirm our commitment to always offer essential financial services and solutions for our customers and communities, including during emergency situations and/or natural disasters. Popular’s employees are considered essential workers, whose role is critical in the continuity of these important services even under such circumstances. By applying to this position, you acknowledge that Popular may require your services during and immediately after any such events.
If you have a disability or need more information about requesting an accommodation, please contact us at asesorialaboral@popular.com. This email inbox is monitored for such types of requests only. All information you provide will be kept confidential and will be used only to the extent required to provide needed exemptions or reasonable accommodations. Any other correspondence will not receive a response.
Are you ready for a rewarding career?
Popular is an Equal Opportunity Employer
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing Agile ANOVA Architecture Avro AWS Azure Big Data Bitbucket Caffe Causal inference Clustering CSV Data analysis Data Analytics Databricks Data governance DataOps DataRobot Data warehouse Deep Learning DevOps Economics ELT ETL GANs GCP Generative AI Git GitLab Hadoop HuggingFace Jenkins Jira JSON Kanban Keras LLMs Machine Learning Mathematics Matplotlib Maven ML models MySQL NLP NumPy Oracle Pandas Parquet PhD Privacy Python PyTorch R Redshift SageMaker SAS Scikit-learn SciPy Scrum Snowflake Spark SQL Statistical modeling Statistics TensorFlow Testing XML
Perks/benefits: Career development Flat hierarchy Team events
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