Senior Machine Learning Engineer at Experian

Heredia, , Costa Rica -

Full Time

Start Date

Immediate

Expiry Date

16 Apr, 26

Salary

0.0

Posted On

16 Jan, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Data Science, Statistical Modeling, Cloud Computing, E-commerce, Digital Marketing, Regression, Support Vector Machines, Neural Nets, Deep Learning, Hadoop, Spark, Numpy, Pandas, SQL, Git

Industry

Information Services

Description

Company Description Experian is a global company in data services, helping organizations and consumers manage risk and make informed decisions. We empower individuals and businesses at important life moments, from purchasing a home to expanding customer bases. With over 125 years of experience, we specialize in data gathering, analysis, and fraud prevention. Our 21,700 employees across 30 countries are dedicated to innovation and creating opportunities for a better tomorrow. Recently ranked the fifth-best company to work for in Costa Rica, we prioritize inclusive culture, employee well-being, and career development. Join us at www.experian.com/careers to be part of our team. Job Description Experian Consumer Services is looking for a Senior Machine Learning Engineer to help create personalized financial solutions to our customers. Extract insights from data and deliver a ML project from beginning to end, including understanding our needs, training/validating ML models, and deploying ML models to applications. Experian is the world's leading global information services company, unlocking the power of data to create more opportunities for consumers, businesses and society. We are thrilled to share that FORTUNE has named Experian one of the 100 Best Companies to work for. Also, for the last five years we've been name in the 100 "World's Most Innovative Companies" by Forbes Magazine. What you'll do Develop machine learning algorithms with huge data sets to solve challenging business questions. Improve performances of existing ML algorithms. Partner with data scientists to discover new data sources and create new input features for ML models. Build end-to-end data pipeline for ML models. Implement experimental systems and evaluate model performances. Communicate results to partners. What your background is Advanced degree in a quantitative field (Machine Learning, Data science, Computer Science) or equivalent professional experience. 5+ years of work experience in data science or statistical modeling using cloud computing services such as AWS, Google Cloud Platform, Snowflake, Databricks. Experience with e-commerce and digital marketing. Experience with statistical modeling techniques such as regression, support vector machines, and neural nets. Experience with deep learning algorithms such as convolutional neural networks and recurrent neural networks. Experience with Hadoop or Spark. Working knowledge of Data Science tools (e.g., Numpy, Pandas, Scikit, Tensorflow, Keras, R). Experience with data processing tools (e.g., SQL). Experience with version control systems (i.e. Git, GitHub) and writing production ready code. Qualifications Advanced degree in a quantitative field (Machine Learning, Data science, Computer Science.) or equivalent professional experience. 5+ years of work experience in a quantitative field such as data science or statistical modeling using cloud computing services such as AWS, Google Cloud Platform, Snowflake, Databricks. Experience with statistical modeling techniques such as regression, support vector machines, and neural nets. Experience with natural language processing is a plus. Experience with deep learning algorithms such as convolutional neural networks and recurrent neural networks is a plus. Experience with group-computing framework, such as Hadoop or Spark. Working knowledge of Data Science tools (e.g., Numpy, Pandas, Scikit, Tensorflow, Keras, and R). Experience with version control systems (i.e. Git, GitHub) and writing production ready code. Additional Information Our uniqueness is that we celebrate yours. Experian's culture and people are important differentiators. We take our people agenda very seriously and focus on what matters; DEI, work/life balance, development, authenticity, collaboration, wellness, reward & recognition, volunteering... the list goes on. Check out Experian Life on social or our Careers Site to understand why. Experian is proud to be an Equal Opportunity and Affirmative Action employer. Innovation is an important part of Experian's DNA and practices, and our diverse workforce drives our success. Everyone can succeed at Experian and bring their whole self to work, irrespective of their gender, ethnicity, religion, colour, sexuality, physical ability or age. If you have a disability or special need that requires accommodation, please let us know at the earliest opportunity. Employee Status: Regular Role Type: Home Department: Product Development Schedule: Full Time Shift: Day Shift

Responsibilities

Develop machine learning algorithms to solve business questions and improve existing ML algorithms. Build end-to-end data pipelines and communicate results to partners.