Jubil ID: 51

Company: MiTek USA

Location: Long Beach, CA

Description:
Job DescriptionAre you ready to lead the charge in transforming the financial services industry with cutting-edge AI and ML solutions? As a Vice President
Applied AI/ML Lead
you'll have the opportunity to tackle exciting business problems in commercial banking
payments
and financial services. Join our dynamic technology team and make a direct impact on global business operations.As a Vice Pr

Qualifications:
6+ years of experience as a Data Scientist Advanced degree in Computer Science
Data Science
or a related field Expertise in Python
PySpark
deep learning frameworks like TensorFlow
and MLOps Experience designing and deploying scalable distributed ML models in production Proficiency in analytics tools such as SQL
Presto
Spark
Python
and AWS suite Familiarity with machine learning techniques and advanced analytics

Benefits:
We offer a competitive total rewards package including base salary determined based on the role
experience
skill set and location Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation
paid in the form of cash and/or forfeitable equity
awarded in recognition of individual achievements and contributions We also offer a range of benefits and programs to meet employee needs
based on eligibility These benefits include comprehensive health care coverage
on-site health and wellness centers
a retirement savings plan
backup childcare
tuition reimbursement
mental health support
financial coaching and more

Responsibilities:
As a Vice President
Applied AI/ML Lead
you'll have the opportunity to tackle exciting business problems in commercial banking
payments
and financial services You will work collaboratively with a team that values innovation and creativity
using your skills to develop and deploy machine learning models that drive business success Build and train production-grade ML models on large-scale datasets for commercial banking use cases Utilize data processing frameworks like Spark and AWS EMR for feature engineering with structured and unstructured data Apply deep learning models such as CNN
RNN
and NLP