<p><span data-sheets-root="1" style="font-size: 11pt; font-family: Arial; background-color: rgb(255, 255, 255);"><font color="#000000">Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scope. Collaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilities<br>Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards<br>Use big data technologies to help process data and build scaled data pipelines (batch to real time)<br>Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines leveraging the NGAA platform (Azure)<br>Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure<br>Automate ML models deployments.</font></span></p><p><span data-sheets-root="1" style="font-size: 11pt; font-family: -apple-system, Arial; background-color: rgb(255, 255, 255);"><font color="#000000">The role will work in developing Machine Learning (ML) and Artificial Intelligence (AI) projects. Specific scope of this role is to develop ML solution in support of ML/AI projects using big analytics toolsets in a CI/CD environment. Analytics toolsets may include DS tools/Spark/Databricks, and other technologies offered by Microsoft Azure or open-source toolsets. This role will also help automate the end-to-end cycle with Azure Machine Learning Services and Pipelines.</font></span></p>
Education: BE/BS in Computer Science, Math, Physics, or other technical fields..
Skill: "Data Science - Hands on experience and strong knowledge of building machine learning models - supervised and unsupervised models. Programming Skills - Hands-on experience in statistical programming languages like Python, R and database query languages like SQL Statistics - Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimators Cloud (Azure) - Experience in Databricks and ADF is desirable Familiarity with Spark, Hive, Pig is an added advantage Model deployment experience will be a plus Experience with version control systems like GitHub and CI/CD tools Experience is Exploratory data Analysis Knowledge of ML Ops / DevOps and deploying ML models is required Experience using MLFlow, Kubeflow etc. will be preferred Experience executing and contributing to ML OPS automation infrastructure is good to have Exceptional analytical and problem-solving skills"
"Strong knowledge of the foodservice and wholesale market.Excellent communication and negotiation skills, with the ability to build relationships with key clients. Self-motivated, goal-oriented, and driven to succeed. Ability to work independently and as part of a team. "