Job Description:

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 Engineers for our team.As part of this job, you will be responsible for:Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutionsCreating Scalable Machine Learning systems that are highly performantBuilding reusable production data pipelines for implemented machine learning modelsWriting production-quality code and libraries that can be packaged as containers, installed and deployedRequirementsEssential Functions Support ML projects from strategy through implementation and on-going improvements. Perform data collection, analysis, validation, cleansing, developing software in support of multiplemachine learning workflows, integrating deployment of code in a large-scale productionenvironments and reporting. Designs, codes, tests, debugs, and documents ML code - models, ETL processes, SQL queries, andstored procedures. Extracts and analyzes data from various structured and unstructured sources, including databases,files, data lakes and external APIswebsites. Responds to data inquiries from various groups within client's organization. Requires experience with relational databases, document databases (NOSQL) and knowledge ofquery tools andor statistical software. Responsible for other dutiesprojects as assigned by business management leadership.QualificationsMinimum Required 7 plus years of experience in statistical modeling, data mining, analytics techniques, machinelearning software development and reporting 5 plus years of applied experience in building deploying Machine Learning solutions usingvarious supervisedunsupervised ML algorithms such as LinearLogistic Regression, SupportVector Machines, (Deep) Neural Networks, Random Forest, etc., and key parameters that affecttheir performance. 5 plus years of hands-on experience with Python andor R programming and statisticalpackages, and ML libraries such as scikit-learn, TensorFlow, PyTorch, etc. 3 plus years of experience in building use cases solutions especially around AIbased on Cloud infrastructure and services such as Azure,GCP,AWS cloud platforms and Onpremiseenvironments Expertise with SQL, noSQL, Python, R, Javascript programming languages and big dataenvironments (such as Splunk, Hadoop, Spark, Flink, Stream Analytics, Kafka, Docker,Kubernetes etc.) Experience developing experimental and analytic plans for data modeling processes, usingstrong baselines, and determining cause and effect relations. Understanding of relevant statistical measures such as confidence intervals, significance of errormeasurements, 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 electricalengineering, mathematics, statistics) or equivalent domain specific experience in lieu of adegree. Proficient in machine learning data workflows, data collection methodologies, and data analysis. Experience with architecting, designing, developing software solution in Azure and on-premenvironments. Certifications AI ML and Azure Cloud platformsBenefitsSignificant 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.