Are you passionate about changing the world through machine learning and location intelligence? If yes, then it’s the right time to join our team because we are about to do so! With the IoT revolution and the consumerization of mapping and location data growing exponentially, location is becoming increasingly important. We want to help organizations and businesses go beyond basic visualization and analytics of massive data to extract advanced levels of intelligence, predict important events, and automate significant portions of their work through AI and machine learning.
We are looking for an entrepreneurial, collaborative person with strong hands-on experience and a solid track record in statistical analysis, machine learning, predictive analytics, software engineering, and a passion for location to assist us in building world-class predictive location analytics solutions for our customers in over 160 countries.
Responsibilities:
- Consult closely with customers to understand their needs.
- Develop and pitch data science solutions by mapping business problems to machine learning or other advanced analytics approaches.
- Build high-quality analytics systems that solve our customers' business problems using techniques from data mining, statistics, and machine learning.
- Write clean, collaborative, and version-controlled code to process big and streaming data from various sources and types.
- Perform feature engineering, model selection, and hyperparameter optimization to yield high predictive accuracy and deploy models to production in cloud, on-premises, or hybrid environments.
- Implement best practices and patterns for geospatial machine learning and develop reusable technical components for demonstrations and rapid prototyping.
- Stay up to date with the latest technology trends in machine and deep learning and incorporate them in project delivery.
Requirements:
- 5+ years of experience with Python in data science and deep learning.
- Experience in building and optimizing supervised and unsupervised machine learning models, including deep learning.
- Fundamental understanding of mathematical and machine learning concepts such as calculus, back propagation, ReLU, Bayes’ theorem, Random Forests, time series analysis, and more.
- Experience with applied statistics concepts.
- Ability to develop software collaboratively in Python using version control.
- Proficiency in data extraction, transformation, loading from multiple sources and sinks.
- Ability to produce data visualizations using tools such as matplotlib.
- Self-motivated, life-long learner with strong communication skills, including to non-technical audiences.
- Bachelor's degree in mathematics, statistics, computer science, physics, or a similar field.
Recommended Qualifications:
- Familiarity with Git, Pytorch, Tensorflow, and CUDA/GPU programming.
- DevOps/MLOps experience using Docker/Kubernetes.
- Experience handling massive batch/streaming data using big data tools such as Apache Spark.
- Experience interacting with AWS, Azure, or other cloud services.
- Experience building reinforcement learning models.
- Familiarity with spatial and GIS concepts, preferably using Esri software.
- Master's degree in mathematics, statistics, computer science, physics, or a similar field.
Language Requirements: Not specified.
Work Conditions: Hybrid, full-time position.
Esri is committed to creating a diverse workforce and believes in inclusivity and continuous improvement in the workplace for all employees. 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.
