What are the responsibilities and job description for the Machine Learning Engineer position at Tiger Analytics?
Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.
We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:
- Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
- Creating Scalable Machine Learning systems that are highly performant
- Building reusable production data pipelines for implemented machine learning models
- Writing production-quality code and libraries that can be packaged as containers, installed and deployed
You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.
Essential Functions
machine learning workflows, integrating / deployment of code in a large-scale productionnvironments and reporting.
stored procedures.
files, data lakes and external APIs/websites.
query tools and/or statistical software.
Qualifications
Minimum Required
learning software development and reporting.
various supervised/unsupervised ML algorithms such as Linear/Logistic Regression, Support
Vector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affect
their performance.
packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc.
based on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremise
environments
environments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker,
Kubernetes etc.)
strong baselines, and determining cause and effect relations.
measurements, development and evaluation data sets, etc. in data analysis projects.
Desired
engineering, mathematics, statistics) or equivalent domain specific experience in lieu of a
degree.
environments.
This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.
