Remote Senior Data Scientist - Telematics

Description:

• Tiger Analytics is seeking a fully remote experienced Telematics Data Scientist to join their advanced analytics consulting firm.
• The firm specializes in Data Science, Machine Learning, and AI, serving multiple Fortune 500 companies.
• The role involves applying expertise in AI through machine learning, data mining, and information retrieval.
• Responsibilities include designing, prototyping, and building advanced analytics engines and services.
• The Data Scientist will collaborate with cross-functional teams to define technical problem statements and hypotheses.
• The position requires developing efficient and accurate analytical models that mimic business decisions.
• The Data Scientist will incorporate these models into analytical data products and tools.
• The role provides an opportunity to influence current and future strategy by leveraging analytical skills and communicating results.

Requirements:

• A Bachelor’s Degree in Computer Science or a closely related field is required.
• Candidates should have 6 to 10 years of experience in Data Science.
• Proficiency in R, Python, or similar programming languages is necessary.
• Experience in vehicle telematics, logistics, pattern detection in sensor or smartphone-connected data, and geospatial mapping is required.
• Candidates should have experience developing computational algorithms to reduce computation time, such as MapReduce.
• Deep expertise with geospatial packages like geopandas and rasterio in Python is a major plus.
• Familiarity with machine learning and deep learning frameworks such as H2O, TensorFlow, PySpark, PyTorch, MXNet, or Caffe is required.
• Understanding of data harmonization challenges and feature preparation from various 3rd party providers is necessary.
• Experience with distributed storage and database platforms is required.
• Candidates should understand how telematics data is leveraged for BI and analytics purposes.
• Experience working with weather and atmospheric data is necessary.
• Familiarity with batch, micro-batch, streaming, and distributed processing platforms like Flink, Hadoop, Kafka, Spark, Hudi, AWS EMR, Arrow, or Storm is required.
• Experience within Amazon Web Services (AWS) cloud computing environments is necessary.
• Candidates should have experience handling terabytes, petabytes, or exabytes of data.
• Familiarity with containerization tools such as Docker and Kubernetes is required.
• A background in spatial optimization algorithms is a major plus.

Benefits:

• This position offers significant career development opportunities in a fast-growing and challenging entrepreneurial environment.
• The role comes with a high degree of individual responsibility, allowing for personal and professional growth.