Remote Data Scientist

Summary

Join Tiger Analytics as a fully remote experienced Telematics Data Scientist to apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services.

Requirements

• Bachelor’s Degree in Computer Science or closely related field
• 6 to 10 years of experience in Data Science
• Experience with R, Python, or similar programming languages
• Experience working in the areas of vehicle telematics, logistics, pattern detection in sensor or smartphone-connected data, and geospatial mapping
• Experience with the development of computational algorithms to reduce computation time (e.g. MapReduce)
• Deep expertise with relevant geospatial packages (e.g. geopandas and rasterio in Python; maptools, spdep, or OpenStreetMap) is a major plus
• Experience with popular machine learning and deep learning frameworks (e.g. H2O, TensorFlow, PySpark, PyTorch, MXNet, Caffe)
• Understanding of the challenges in data harmonization and feature preparation from variety of 3rd party providers
• Experience with distributed storage and database platforms
• Understanding how the telematics data gets leveraged downstream for BI (trip completion) and analytics purposes (pricing)
• Experience working with weather and atmospheric data
• Experience with batch, micro-batch, streaming, and distributed processing platforms such as Flink, Hadoop, Kafka, Spark, Hudi, AWS EMR, Arrow, or Storm
• Experience working within Amazon Web Services (AWS) cloud computing environments
• Experience with terabytes, petabytes, or even exabytes of data
• Familiarity with containerization tools such as Docker and Kubernetes
• Background in spatial optimization algorithms is a major plus

Responsibilities

• Apply strong expertise in AI through the use of machine learning, data mining, and information retrieval to design, prototype, and build next generation advanced analytics engines and services
• Collaborate with cross-functional teams and business partners to define the technical problem statement and hypotheses to test
• Develop efficient and accurate analytical models which mimic business decisions and incorporate those models into analytical data products and tools
• Drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results