Data Scientist

Esri; Redlands, California, New York (CA, MO, NY); On-site; USD 95,000 - 165,000; Full time

Job summary

Join a forward-thinking company as a Machine Learning Engineer, where your expertise in statistical analysis and predictive analytics will drive innovative solutions. Collaborate with a talented team to build and optimize machine learning models that enhance business intelligence. This role offers the chance to work with cutting-edge technologies, including deep learning and cloud services, in a dynamic environment committed to diversity and inclusion. If you're passionate about leveraging data to create impactful solutions, this opportunity is perfect for you.

Benefits

Medical Insurance

Dental Insurance

Vision Insurance

401(k) Plan

Profit Sharing

Paid Vacation

Paid Holidays

Professional Growth Opportunities

Qualifications

• 5+ years of practical machine learning experience.
• Strong understanding of mathematical and machine learning concepts.
• Proficient in SQL, Python, and various machine learning frameworks.

Responsibilities

• Consult with colleagues to understand analytics needs.
• Research appropriate analytics techniques based on data outcomes.
• Develop processes to monitor and analyze model performance.

Skills

Machine Learning

Statistical Analysis

Predictive Analytics

Software Engineering

SQL

Python

PySpark

Natural Language Processing

Feature Engineering

Deep Learning

Education

Bachelor's in Mathematics

Bachelor's in Statistics

Bachelor's in Computer Science

Tools

PyTorch

TensorFlow

Apache Spark

Git

AWS

Azure

Job description

Overview

Our Business Intelligence team are looking for an entrepreneurial, collaborative person with strong hands-on experience and solid track record with statistical analysis, machine learning, predictive analytics, and software engineering to help us on our mission to build world class predictive solutions for the enterprise.

Responsibilities

• Consult closely with colleagues to understand their needs


• Research and determine the appropriate analytics based on the data and the desired outcomes, using techniques including feature detection, statistics, data mining, predictive modeling, machine learning, natural language processing, and business intelligence


• Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy and deploy the model to production in a cloud


• Write custom programs using supervised and unsupervised algorithms to build machine-learning models that optimize outcomes and deliver refined results


• Develop processes and tools to monitor and analyze model performance and data accuracy. Mine data using advanced techniques such as Regression, Clustering, Random Forest, Text Mining, NLP, and Neural Networks to provide in-depth insights from data

Requirements

• 5+ years of practical machine learning experience


• Experience in building and optimizing supervised and unsupervised machine learning models including deep learning and various other modern data science techniques


• A fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, ReLU, Bayes' theorem, Random Forests, time series analysis, and more


• Proficient in SQL, Python, PySpark, PyTorch, PyTorch Lightning, Scikit, Distributed Data Parallel, Distributed Model Parallel


• Strong communication skills, including to non-technical audiences


• Visa sponsorship is not available for this posting. Applicants must be authorized to work for any employer in the US


• Bachelor's in mathematics, statistics, computer science, or a similar field

Recommended Qualifications

• Familiarity with one or more of the following: Git, Pytorch, Tensorflow, CUDA/GPU programming


• Experience handling massive batch/streaming data using big data tools and storage, such as Apache Spark


• Experience interacting with AWS, Azure, Fabric, or other cloud service


• Experience building reinforcement learning models

#LI-JH2

#LI-Onsite

Total Rewards

Esri's competitive total rewards strategy includes industry-leading health and welfare benefits: medical, dental, vision, basic and supplemental life insurance for employees (and their families), 401(k) and profit-sharing programs, minimum accrual of 80 hours of vacation leave, twelve paid holidays throughout the calendar year, and opportunities for personal and professional growth. Base salary is one component of our total rewards strategy. Compensation decisions and the base range for this role take into account many factors including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs.

A reasonable estimate of the base salary range is

$95,680—$164,320 USD

The Company

At Esri, diversity is more than just a word on a map. When employees of different experiences, perspectives, backgrounds, and cultures come together, we are more innovative and ultimately a better place to work. We believe in having a diverse workforce that is unified under our mission of creating positive global change. We understand that diversity, equity, and inclusion is not a destination but an ongoing process. We are committed to the continuation of learning, growing, and changing our workplace so every employee can contribute to their life's best work. Our commitment to these principles extends to the global communities we serve by creating positive change with GIS technology. For more information on Esri's Racial Equity and Social Justice initiatives, please visit our website here.

If you don't meet all of the preferred qualifications for this position, we encourage you to still apply!

Esri is an equal opportunity employer (EOE) and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. If you need reasonable accommodation for any part of the employment process, please email [e-mail] and let us know the nature of your request and your contact information. Please note that only those inquiries concerning a request for reasonable accommodation will be responded to from this e-mail address.

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