Data Scientist

Popular; Charlotte (NC); Remote; USD 80,000 - 110,000; Full time

Job summary

Join a leading financial institution in Charlotte as a Data Scientist. In this role, you'll leverage your expertise in data analysis and machine learning to provide actionable insights and solutions alongside cross-functional teams. With a commitment to innovation and community support, your work will directly impact clients' lives through effective data strategies and operational excellence.

Qualifications

• 2+ years experience in Quantitative Analytics or decision sciences.
• Hands on with analytics tools and programming languages such as R, Python, SAS, and SQL.
• Proficient in machine learning techniques and algorithms.

Responsibilities

• Conduct thorough exploratory data analysis (EDA) to uncover insights.
• Design, develop, and deploy predictive models and machine learning algorithms.
• Collaborate with teams to understand objectives and develop analytic models.

Skills

Data Analysis

Machine Learning

Statistical Modeling

Programming

Problem Solving

Data Visualization

Education

Bachelor's degree in Statistics

Master's Degree in Data Science

Tools

Python

R

SQL

SAS

TensorFlow

PyTorch

Hadoop

Job description

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Location:

Charlotte, NC, US, 28210

Company: Popular

Workplace Type: Remote

Data Scientist

At Popular, we offer a wide variety of services and financial solutions to serve our communities in Puerto Rico, United States & Virgin Islands. 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; this is why we value their diverse skills, experiences and backgrounds.

Are you ready for a rewarding career?

We have more than 9,000 people working for Popular in Puerto Rico, United States, Virgin Islands and Latin America.

Come and join our community!

The Opportunity

Data Scientist I is a role that involves working on data analysis and model development under the supervision of senior team members. With a deep understanding of data science and machine learning workflows, you'll build and lead by example, fostering a culture of operational excellence. This highly cross-functional role requires strong partnerships with engineering, products, business, finance, and analytics teams, as well as accountability, and the ability to navigate fast-paced environments with agility and poise.

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.

Specifically:

Conduct thorough exploratory data analysis (EDA) to uncover insights and inform model development.

· Hands on design, development, and deployment of predictive models, machine learning algorithms, and AI solutions.

· Collaborate with team members and business stakeholders to understand objectives and requirements and develop analytic models that provide actionable insights.

· Ensure the validity, reliability, and robustness of models by implementing best practices in model validation, testing, and calibration.

· Partner with the Advanced Analytics Center of Excellence to share knowledge, best practices, and resources.

· Monitor performance and outcomes of models and refine them for optimized performance.

· Communicate complex analytic solutions and insights in a clear and structured manner to business stakeholders.

· Ensure compliance with data governance, privacy, and security policies.

To qualify for the role, you must have:

· Bachelor's degree or Master's Degree in Statistics, Mathematics, Data Science, Economics, or a related field.

· A minimum of 2 years of experience in Quantitative Analytics or decision sciences

· Hands on experience with analytics tools and programming languages such as R, Python, SAS, and SQL.

· Proficiency in machine learning techniques and algorithms, including but not limited to k-NN, Naive Bayes, SVM, and Decision Forests.

· Solid understanding of cloud computing environments and experience with deploying models in cloud environments such as AWS, Azure, or GCP.

· Experience of one or more AI/ML platforms in cloud such as Sagemaker, Dataiku, DataRobot, H2O.ai, Snowpark, ModelOp Center, and Domino Data Lab.

· Strong knowledge of statistical modeling, machine learning algorithms, and data analysis techniques.

· 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.

· Experience in following waterfall, iterative, scaled agile, scrum, and kanban methodologies.

· 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.

· Experience with Graph Networks, Fraud detection, financial crimes implementations

· Proficiency in 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).

· Implemented machine learning models by leveraging algorithms such as Linear Regression, Decision tree, SVM, Clustering, Naive Bayes, KNN, Random Forest, PCA, AdaBoost.

· 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

· 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.

· Demonstrated experience in Hadoop, EMR (Elastic MapReduce), EKS (Elastic Kubernetes Service), ECS (Elastic Container Service), Docker, Kubernetes, and Amazon Sagemaker for visionary, scalable, and efficient machine learning workflows.

· 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.

· Knowledge of big data technologies such as Hadoop, Spark, or similar.

· Excellent analytical and problem-solving skills.

· Ability to communicate and collaborate with diverse set of team members.

What we look for:

We are seeking enthusiastic candidates who have 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. 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.

Important: The candidate must provide evidence of academic preparation or courses related to the job posting, if necessary.

If you have a disability and need assistance with the application process, please contact us at [e-mail] . 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 reasonable accommodations. Any other correspondence will not receive a response.

As a leading financial institution in the communities we serve, we reaffirm our commitment to always offer essential financial services and solutions for our customers, 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 are a California resident, pleaseclick here to learn more about your privacy rights.

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Popularis an Equal Opportunity Employer