Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.We are looking for a motivated and passionate Machine Learning Engineer for our team. As part of this job, you will be responsible for:<ul> <li>Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions</li> <li>Creating scalable Machine Learning systems that are highly performant</li> <li>Building reusable production data pipelines for implemented machine learning models</li> <li>Writing production-quality code and libraries that can be packaged as containers, installed and deployed</li> </ul>Essential Functions:<ul><li>Support ML projects from strategy through implementation and ongoing improvements.</li><li>Perform 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.</li><li>Design, code, test, debug, and document ML code - models, ETL processes, SQL queries, and stored procedures.</li><li>Extract and analyze data from various structured and unstructured sources, including databases, files, data lakes, and external APIs/websites.</li><li>Respond to data inquiries from various groups within the client’s organization.</li><li>Requires experience with relational databases, document databases (NoSQL), and knowledge of query tools and/or statistical software.</li><li>Responsible for other duties/projects as assigned by business management/leadership.</li></ul>Qualifications:Minimum Required:<ul><li>7 plus years of experience in statistical modeling, data mining, analytics techniques, machine learning software development, and reporting.</li><li>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.</li><li>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.</li><li>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 on-premise environments.</li><li>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.).</li><li>Experience developing experimental and analytic plans for data modeling processes, using strong baselines, and determining cause and effect relations.</li><li>Understanding of relevant statistical measures such as confidence intervals, significance of error measurements, development and evaluation data sets, etc. in data analysis projects.</li><li>Expertise with scaling pilot machine learning solutions to a large-scale production environment using Databricks.</li><li>Expertise with visualization tools such as PowerBI, D3JS, etc.</li><li>Excellent written and verbal communication skills.</li></ul>Desired:<ul><li>Bachelor's or Master's degree in a highly quantitative field (computer science, electrical engineering, mathematics, statistics) or equivalent domain-specific experience in lieu of a degree.</li><li>Proficient in machine learning data workflows, data collection methodologies, and data analysis.</li><li>Experience with architecting, designing, developing software solutions in Azure and on-prem environments.</li><li>Certifications in AI/ML and Azure Cloud platforms.</li></ul>Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging, and entrepreneurial environment, with a high degree of individual responsibility.
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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.

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.

Experience :6.5 to 11 YearsLocation: Chennai, Bengaluru, and HyderabadAbout Roles : We are looking for a Senior / Lead ML Engineer who will work on a broad range of cutting-edge data analytics and machine learning problems across a variety of industries.More specifically, you will<ul><li>Engage with clients to understand their business context</li><li>Lead a team of data scientists and engineers to embed AI and analytics into the business decision processes.</li><li>Perform a role that involves a combination of hands-on contribution and customer engagement.</li><li>Switch between roles of an Individual Contributor, team member and solution architect as demanded by each project </li></ul>Skill Expertise : <ul><li>6+ years exp of which 3+ years of relevant data science experience and at least 3 years of software development experience.</li><li>Experience in devising creative analytical approaches to solve business problems</li><li>Developing and enhancing algorithms and models to solve business problem</li><li>Maintaining all models along with development and updating of code and process documentation</li><li>Designing a solution approach, leading a team to deploy and maintain it in production.</li><li>Proficient in Structured programming language is a must - such as Python, C/C++, Java is mandatory.</li><li>Cloud concepts and significant hands-on experience with at least one cloud provider. Should be knowledgeable about the pros and cons of the various services and comfortable discussing the tradeoffs with stakeholders.</li><li>Strong SQL skills.</li><li>Good knowledge of Data science approaches, machine learning algorithms and statistical methods.</li><li>ETL and Data Engineering pipelines using Spark/PySpark.</li><li>Workflow orchestration tools like Airflow.</li><li>Excellent written and verbal communication skills</li><li>B. Tech from Tier-1 college / M.S or M. Tech is preferred</li></ul>

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 Bachelor's degree or higher in computer science or related, with 5 years of work experience Ability to collaborate with Data Engineers and Data Scientists to build data and model pipelines and help run machine learning tests and experiments Ability to manage the infrastructure and data pipelines needed to bring ML solutions to production End-to-end understanding of applications being created Ability to maintain scalable machine learning solutions in production Ability to abstract the complexity of production for machine learning using containers Ability to troubleshoot production machine learning model issues, including recommendations for to retrain and revalidate Experience with Big Data Projects using multiple types of structured and unstructured data Ability to work with a global team, playing a key role in communicating problem context to the remote teams Excellent communication and teamwork skills Additional Skills Required Python, Spark, Hadoop, and Docker with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design Knowledge of ML frameworks like Scikitlearn, Tensorflow, and Keras Knowledge of MLflow, Airflow, and Kubernetes Experience with Cloud environments and knowledge of offerings such as AWS SageMaker Proficiency in statistical tools, relational databases, and expertise in programming languages (Python/SQL) 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.

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: <ul> <li>Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions</li> <li>Creating Scalable Machine Learning systems that are highly performant</li> <li>Building reusable production data pipelines for implemented machine learning models</li> <li>Writing production-quality code and libraries that can be packaged as containers, installed and deployed</li> </ul>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 <ul> <li>Bachelor's degree or higher in computer science or related, with 5+ years of work experience</li> <li>Ability to collaborate with Data Engineers and Data Scientists to build data and model pipelines and help run machine learning tests and experiments</li> <li>Ability to manage the infrastructure and data pipelines needed to bring ML solutions to production</li> <li>End-to-end understanding of applications being created</li> <li>Ability to maintain scalable machine learning solutions in production</li> <li>Ability to abstract the complexity of production for machine learning using containers</li> <li>Ability to troubleshoot production machine learning model issues, including recommendations for to retrain and revalidate</li> <li>Experience with Big Data Projects using multiple types of structured and unstructured data</li> <li>Ability to work with a global team, playing a key role in communicating problem context to the remote teams</li> <li>Excellent communication and teamwork skills</li> </ul>Additional Skills Required<ul> <li>Python, Spark, Hadoop, and Docker with an emphasis on good coding practices in a continuous integration context, model evaluation, and experimental design</li> <li>Knowledge of ML frameworks like Scikitlearn, Tensorflow, and Keras</li> <li>Knowledge of MLflow, Airflow, and Kubernetes</li> <li>Experience with Cloud environments and knowledge of offerings such as AWS SageMaker</li> <li>Proficiency in statistical tools, relational databases, and expertise in programming languages (Python/SQL)</li> </ul> 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. #LI-remote

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