Software Development Engineering - Advisor II

FiservMilwaukee, WI
Onsite

About The Position

We're Fiserv, a global leader in Fintech and payments, and we move money and information in a way that moves the world. We connect financial institutions, corporations, merchants and consumers to one another millions of times a day - quickly, reliably, and securely. Any time you swipe your credit card, pay through a mobile app, or withdraw money from the bank, we're involved. If you want to make an impact on a global scale, come make a difference at Fiserv.

Requirements

  • Bachelor's degree in Computer Engineering, Telecommunications Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, Statistics, Mathematics, Applied Mathematics, Physics, or a related field and 4 years in any job title involving algorithm, machine learning framework, and platform development experience in data science.
  • Alternatively, the employer will accept Master’s degree in Computer Engineering, Telecommunications Engineering, Electrical Engineering, Mechanical Engineering, Computer Science, Data Science, Statistics, Mathematics, Applied Mathematics, Physics, or a related field and 2 years in any job title involving algorithm, machine learning framework, and platform development experience in data science.
  • Prior experience must include: 2 years developing and deploying data science models using Python; 2 years working with version control systems including GIT; 2 years documenting the development processes, including code, design decisions, and user guides; 2 years working in Machine Learning (ML), natural language processing (NLP), and deep learning (DL) models for business specific use cases; 1 year designing and building topic modeling algorithms using Latent Dirichlet Allocation (LDA); Designing and creating Sigma dashboard to showcase topic modeling results for stakeholders; Performing analysis on topic modeling outputs to derive actionable insights and present findings to stakeholders; Presenting highly technical findings to non-technical audience including senior leadership; Performing Exploratory Data Analysis (EDA) on numerical and categorical features to identify relevant features; Designing and developing ensemble model to predict merchant attrition risk; Designing, developing and deploying merchant retention models to predict customer retention using Adobe Analytics; Designing and developing clustering algorithm on a set of customers identified by merchant retention model based on heuristics and business requirements; Designing KPIs based on customer behavior data to measure performance and customer stickiness; Designing and building database structure and automated reporting dashboard using tableau and sigma; Designing and developing Random Forest and Regression model to predict customer/merchant retention; Designing and developing time series model using ARIMA and fbProphet for multi-region demand forecasting at multiple temporal resolution; Working with TensorFlow, scikit-learn, and Keras for machine learning tasks; Implementing web scraping and data mining solutions to gather open-source data using scrapy in Python; Leading and performing architectural design with collaborators based on stakeholder requirements; and Performing text preprocessing, vectorization using Tf-Idf, clustering using DBScan, and summarization methods.

Responsibilities

  • Spearhead and fine tune the creation of emerging deep learning models that transform text, raw images, and time series data into interpretable information and actionable recommendations to power AI applications.
  • Design and implement user-friendly interactive web applications that connect with machine learning systems.
  • Deploy deep learning models.
  • Design and implement dashboards to summarize key analytics for stakeholders.
  • Collaborate with product, engineering, and operational teams to proactively gather feedback, gather requirements, and develop metrics.
  • Communicate findings, recommendations, and analysis results to stakeholders in verbal, visual and written media.
  • Stay up-to-date with industry trends and advancements in machine learning platforms as well as machine learning techniques, and lead the team in learning and improvement.
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