Data Science Architect for Large-Scale Analytics Solutions

3 days ago

Seattle, Washington, United States Tiger Analytics Full time

Tiger Analytics is a leading advanced analytics consulting firm, trusted by several Fortune 100 companies to unlock business value from data. Our team of experts brings deep expertise in Data Science, Machine Learning, and AI.

We are seeking an experienced Machine Learning Engineer to join our team.

The successful candidate will be responsible for:

  • Designing and implementing scalable Machine Learning systems that meet high performance standards
  • Developing reusable production data pipelines for implemented machine learning models
  • Writing production-quality code and libraries that can be packaged as containers, installed, and deployed

Key responsibilities include:

  • Supporting ML projects from strategy through implementation and ongoing improvements
  • Performing data collection, analysis, validation, cleansing, and developing software in support of multiple machine learning workflows, integrating/deployment of code in large-scale production environments and reporting
  • Designing, coding, testing, debugging, and documenting ML code - models, ETL processes, SQL queries, and stored procedures
  • Extracting and analyzing data from various structured and unstructured sources, including databases, files, data lakes, and external APIs/websites
  • Responding to data inquiries from various groups within the client's organization

To be considered for this role, you must have:

At least 7 years of experience in statistical modeling, data mining, analytics techniques, machine learning software development, and reporting

5+ years of applied experience in building/deploying Machine Learning solutions using various supervised/unsupervised ML algorithms, including Linear/Logistic Regression, Support Vector Machines, (Deep) Neural Networks, Random Forest, etc.

Hands-on experience with Python and/or R programming and statistical packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.

Experience in building use cases/solutions especially around AI based on Cloud infrastructure and services such as Azure, GCP, AWS cloud platforms and on-premise environments

Expertise with SQL, NoSQL, Python, R, JavaScript programming languages and big data environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker, Kubernetes, etc.)

Excellent written and verbal communication skills

Estimated salary: $150,000 - $180,000 per year

This is a unique opportunity to join a small, fast-growing, challenging, and entrepreneurial environment with a high degree of individual responsibility.

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