Machine Learning Engineer

Where good people build rewarding careers.

Think that working in the insurance field can't be exciting, rewarding and challenging? Think again. You'll help us reinvent protection and retirement to improve customers' lives. We'll help you make an impact with our training and mentoring offerings. Here, you'll have the opportunity to expand and apply your skills in ways you never thought possible. And you'll have fun doing it. Join a company of individuals with hopes, plans and passions, all using and developing our talents for good, at work and in life.

Job Description

  • Learn business concepts and domains quickly.
  • Understand business problems to identify the optimal modeling approach.
  • Perform data preparation using packages such as Numpy, Scipy, pandas, dplyr.
  • Visualize data using packages such as plotly, ggplot2, Matplotlib.
  • Code and develop machine learning prototypes in languages such as Python, R, SAS, Java.
  • Utilize machine learning frameworks such as Keras, Tensorflow, SciKit-Learn, Caffe, MXNet.
  • Learn and gain a functional understanding of supporting technologies to achieve results (e.g. Jupyter, R-Studio, Hadoop, Spark, Kafka, Sagemaker etc.)
  • Identify new areas of data, research and models that can solve business problems.
  • Ability to understand data requests and make recommendations on improving its quality.
  • Aptitude for trouble-shooting and problem-solving.
  • Collaborate with team in order to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling.
  • Work with stakeholders to ensure the machine learning solutions meet business needs.
  • Utilizes effective project planning techniques to break down moderately complex and occasionally complex projects into tasks and ensure deadlines are kept.
  • Creating and maintaining clear and concise technical documentation.
  • Have excellent teamwork and interpersonal skills.


Job Qualifications

  • Bachelor's or Master's Degree in a quantitative field such as statistics, mathematics, Electrical Engineering, Physics or computer science preferred.
  • Solid mathematics background (linear algebra, probability, optimization).
  • Good knowledge of statistics skills, such as distributions, statistical testing, regression, etc.
  • Experience using statistical modeling or machine learning techniques to build models that have driven company decision making.
  • Excellent understanding of machine learning techniques and algorithms such as k-NN, Naïve Bayes, SVM, Decision Forests, CNN etc.
  • Experience with and implementing feature detection and classification.
  • Fundamental understanding of database concepts and technologies.
  • Experience working in an Agile framework is a plus.
  • Experience with evaluating and tuning deployed machine learning models is a plus


The candidate(s) offered this position will be required to submit to a background investigation, which includes a drug screen.

Good Work. Good Life. Good Hands®.

As a Fortune 100 company and industry leader, we provide a competitive salary - but that's just the beginning. Our Total Rewards package also offers benefits like tuition assistance, medical and dental insurance, as well as a robust pension and 401(k). Plus, you'll have access to a wide variety of programs to help you balance your work and personal life -- including a generous paid time off policy.

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Allstate generally does not sponsor individuals for employment-based visas for this position.

Effective July 1, 2014, under Indiana House Enrolled Act (HEA) 1242, it is against public policy of the State of Indiana and a discriminatory practice for an employer to discriminate against a prospective employee on the basis of status as a veteran by refusing to employ an applicant on the basis that they are a veteran of the armed forces of the United States, a member of the Indiana National Guard or a member of a reserve component.

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It is the policy of Allstate to employ the best qualified individuals available for all jobs without regard to race, color, religion, sex, age, national origin, sexual orientation, gender identity/gender expression, disability, and citizenship status as a veteran with a disability or veteran of the Vietnam Era.


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