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Finance Machine Learning Engineer

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Apple

16d ago

  • Job
    Full-time
    Senior Level
  • Banking & Finance
  • Austin

Requirements

  • 5+ Years of relevant experience
  • Bachelor's in Computer Science or other related quantitative field
  • Preferred Qualifications:
  • Efficient python (or equivalent scripting language) programmer experience
  • Effective writing SQL in data warehouse and cloud environments
  • Experience with the ML ops lifecycle – specifically as it relates to automated deployment, testing, concept drift monitoring and proactive model maintenance
  • Practical experience applying, and theoretical understanding of machine learning algorithms and statistical methods for regression, classification, and outlier detection
  • Foundational knowledge of efficient data models for analytics and the ability to build batch type, orchestrated data integrations
  • Understanding of data validations and automated monitoring to ensure integrity and consistency in data pipelines
  • Previous accounting experience or experience working in a corporate finance or accounting organization is a plus.
  • Understanding of or ability to learn high level accounting principles, SOX and tax compliance and month-end close process is a plus.

Responsibilities

  • This role will require you to be collaborative by learning intra-team and business process in order to build infrastructure and services to enable an effective Machine Learning practice. You will help lead the charge by developing a strong ML Ops process in a dynamic Finance environment where you will deal with unique challenges specific to Finance organizations, such as SOx and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.
  • You are a quantitatively and technically inclined individual with an applied data science and/or software engineering background. A good understanding of data engineering principles is important as you will often be responsible for creating your own data models or working with data engineering to optimize internal team frameworks and services. A love for testing, validation and configuration as code will set you apart. You are not required to be an expert in one field, rather, your ability to learn and problem solve is much more desirable. Additionally, the ability to partner and share your expertise with others will help you succeed.This role will require you to be collaborative by learning intra-team and business process in order to build infrastructure and services to enable an effective Machine Learning practice. You will help lead the charge by developing a strong ML Ops process in a dynamic Finance environment where you will deal with unique challenges specific to Finance organizations, such as SOx and regulatory compliance. Your ability to instill and proliferate strong software engineering practices into team data science and machine learning processes will be critical.
  • You are a quantitatively and technically inclined individual with an applied data science and/or software engineering background. A good understanding of data engineering principles is important as you will often be responsible for creating your own data models or working with data engineering to optimize internal team frameworks and services. A love for testing, validation and configuration as code will set you apart. You are not required to be an expert in one field, rather, your ability to learn and problem solve is much more desirable. Additionally, the ability to partner and share your expertise with others will help you succeed.

Technology
Industry
10,001+
Employees
1976
Founded Year

Mission & Purpose

We’re a diverse collective of thinkers and doers, continually reimagining what’s possible to help us all do what we love in new ways. And the same innovation that goes into our products also applies to our practices — strengthening our commitment to leave the world better than we found it. This is where your work can make a difference in people’s lives. Including your own. Apple is an equal opportunity employer that is committed to inclusion and diversity.