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Full Stack Data Scientist

Allstate Insurance Company

United States

Remote

USD 78,000 - 143,000

Full time

10 days ago

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Job summary

Allstate Insurance Company seeks a Full Stack Data Scientist responsible for data-driven solutions, including model development and cloud optimization. The ideal candidate will leverage machine learning techniques to enhance business processes, working alongside a dedicated team in a flexible and inclusive environment.

Qualifications

  • Masters Degree preferred.
  • 2 or more years of experience preferred.
  • Equivalent combination of education and experience may be considered.

Responsibilities

  • Develops end-to-end data-driven solutions and maintains scalable predictive systems.
  • Collaborates to improve business decision-making using data and predictive modeling.
  • Innovates on projects by employing new modeling techniques.

Skills

Business Case Analyses
Data Analytics
Data Science
Machine Learning
Predictive Analytics
Predictive Modeling
Python
Waterfall Project Management

Education

Masters Degree

Job description

At Allstate, great things happen when our people work together to protect families and their belongings from life’s uncertainties. And for more than 90 years our innovative drive has kept us a step ahead of our customers’ evolving needs. From advocating for seat belts, air bags and graduated driving laws, to being an industry leader in pricing sophistication, telematics, and, more recently, device and identity protection.

Job Description

As a Full Stack Data Scientist, you'll be responsible for working as part of a team to develop end-to-end data-driven solutions, from data collection and model development to deployment and maintenance of business-facing inference services. The ideal candidate will have experience developing and implementing cloud-based solutions, optimizing data models for cloud performance, and maintaining scalable predictive systems. As a technical contributor, this role will also begin to manage projects of small to medium complexity.
Key Responsibilities

• Collaborates with the team in order to improve the effectiveness of business decisions through the use of data and machine learning/predictive modeling

• Reviews, evaluates and communicates appropriateness of modeling techniques and results to team and leadership to ensure these are well understood and incorporated into business processes

• Uses best practices, with limited coaching, to develop statistical, machine learning techniques to build models that address business needs and executes on modeling/machine learning projects effectively, contributing to a wide variety of projects

• Utilizes effective project planning techniques to break down basic and occasionally moderately complex machine learning/predictive modeling and/or development projects into tasks and ensure deadlines are kept

• Innovates on projects by using new modeling techniques or tools

Education

• Masters Degree (Preferred)

Experience

• 2 or more years of experience (Preferred)

Education & Experience (in lieu)

• In lieu of the above education requirements, an equivalent combination of education and experience may be considered.

#LI-TE1

Skills

Business Case Analyses, Data Analytics, Data Science, Machine Learning, Machine Learning Techniques, Predictive Analytics, Predictive Modeling, Python (Programming Language), Waterfall Project Management

Compensation

Compensation offered for this role is $78,600.00 - 142,275.00 annually and is based on experience and qualifications.

The candidate(s) offered this position will be required to submit to a background investigation.

Joining our team isn’t just a job — it’s an opportunity. One that takes your skills and pushes them to the next level. One that encourages you to challenge the status quo. And one where you can impact the future for the greater good.

You’ll do all this in a flexible environment that embraces connection and belonging. And with the recognition of several inclusivity and diversity awards, we’ve proven that Allstate empowers everyone to lead, drive change and give back where they work and live.

Good Hands. Greater Together.

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.

For jobs in San Francisco, please click “here” for information regarding the San Francisco Fair Chance Ordinance.
For jobs in Los Angeles, please click “here” for information regarding the Los Angeles Fair Chance Initiative for Hiring Ordinance.

To view the “EEO is the Law” poster click “here”. This poster provides information concerning the laws and procedures for filing complaints of violations of the laws with the Office of Federal Contract Compliance Programs

To view the FMLA poster, click “here”. This poster summarizing the major provisions of the Family and Medical Leave Act (FMLA) and telling employees how to file a complaint.

It is the Company’s policy to employ the best qualified individuals available for all jobs. Therefore, any discriminatory action taken on account of an employee’s ancestry, age, color, disability, genetic information, gender, gender identity, gender expression, sexual and reproductive health decision, marital status, medical condition, military or veteran status, national origin, race (include traits historically associated with race, including, but not limited to, hair texture and protective hairstyles), religion (including religious dress), sex, or sexual orientation that adversely affects an employee's terms or conditions of employment is prohibited. This policy applies to all aspects of the employment relationship, including, but not limited to, hiring, training, salary administration, promotion, job assignment, benefits, discipline, and separation of employment.

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