Tiger Analytics
Machine Learning Engineer
Tiger Analytics, Dallas, Texas, United States, 75215
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.
Requirements
Essential Functions Support ML projects from strategy through implementation and on-going improvements. Perform data collection, analysis, validation, cleansing, developing software in support of multiple
machine learning workflows, integrating / deployment of code in a large-scale productionnvironments and reporting. Designs, codes, tests, debugs, and documents ML code - models, ETL processes, SQL queries, and
stored procedures. Extracts and analyzes data from various structured and unstructured sources, including databases,
files, data lakes and external APIs/websites. Responds to data inquiries from various groups within client's organization. Requires experience with relational databases, document databases (NOSQL) and knowledge of
query tools and/or statistical software. Responsible for other duties/projects as assigned by business management / leadership.
Qualifications
Minimum Required 7 plus years of experience in statistical modeling, data mining, analytics techniques, machine
learning software development and reporting. 5 plus years of applied experience in building / deploying Machine Learning solutions using
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. 5 plus years of hands-on experience with Python and/or R programming and statistical
packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc. 3 plus years of experience in building use cases / solutions especially around AI/
based on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremise
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.) Experience developing experimental and analytic plans for data modeling processes, using
strong baselines, and determining cause and effect relations. Understanding of relevant statistical measures such as confidence intervals, significance of error
measurements, development and evaluation data sets, etc. in data analysis projects. Expertise with scaling pilot machine learning solutions to a large scale production environment using databricks Expertise with visualization tools such as PowerBI, D3JS etc. Excellent written and verbal communication skills.
Desired Bachelor or Masters degree in highly quantitative field (computer science, or electrical
engineering, mathematics, statistics) or equivalent domain specific experience in lieu of a
degree. Proficient in machine learning data workflows, data collection methodologies, and data analysis. Experience with architecting, designing, developing software solution in Azure and on-prem
environments. Certifications AI / ML and Azure Cloud platforms
Benefits
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.
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.
Requirements
Essential Functions Support ML projects from strategy through implementation and on-going improvements. Perform data collection, analysis, validation, cleansing, developing software in support of multiple
machine learning workflows, integrating / deployment of code in a large-scale productionnvironments and reporting. Designs, codes, tests, debugs, and documents ML code - models, ETL processes, SQL queries, and
stored procedures. Extracts and analyzes data from various structured and unstructured sources, including databases,
files, data lakes and external APIs/websites. Responds to data inquiries from various groups within client's organization. Requires experience with relational databases, document databases (NOSQL) and knowledge of
query tools and/or statistical software. Responsible for other duties/projects as assigned by business management / leadership.
Qualifications
Minimum Required 7 plus years of experience in statistical modeling, data mining, analytics techniques, machine
learning software development and reporting. 5 plus years of applied experience in building / deploying Machine Learning solutions using
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. 5 plus years of hands-on experience with Python and/or R programming and statistical
packages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc. 3 plus years of experience in building use cases / solutions especially around AI/
based on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremise
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.) Experience developing experimental and analytic plans for data modeling processes, using
strong baselines, and determining cause and effect relations. Understanding of relevant statistical measures such as confidence intervals, significance of error
measurements, development and evaluation data sets, etc. in data analysis projects. Expertise with scaling pilot machine learning solutions to a large scale production environment using databricks Expertise with visualization tools such as PowerBI, D3JS etc. Excellent written and verbal communication skills.
Desired Bachelor or Masters degree in highly quantitative field (computer science, or electrical
engineering, mathematics, statistics) or equivalent domain specific experience in lieu of a
degree. Proficient in machine learning data workflows, data collection methodologies, and data analysis. Experience with architecting, designing, developing software solution in Azure and on-prem
environments. Certifications AI / ML and Azure Cloud platforms
Benefits
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.