Data Science Analyst @ JPMorgan

Job Description

Overview Main Purpose: 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. Responsibilities Key Accountabilities: 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 Ensure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standards Use big data technologies to help process. data and build scaled data pipelines (batch to real time) Automate the end-to-end ML lifecycle with Azure Machine Learning and Azure Pipelines leveraging the NGAA platform (Azure) Setup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructure Automate ML models deployments Qualifications 4 - 7 years of overall experience that includes at least 4+ years of hands-onwork experience data science /Machine learning Minimum4+ year of SQL experience Experience in DevOps and Machine Learning (ML) with hands-on experience with one or more cloud service providers (Azure preferred) is preferred BE/BS in Computer Science, Math, Physics, or other technical fields. Skills, Abilities, Knowledge 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 , R and database query languages like 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 Differentiating Competencies Required Ability to work with virtual teams (remote work locations) lead team of technical resources (employees and contractors) based in multiple locations across geographies Lead technical discussions, driving clarity of complex issues/requirements to build robust solutions Strong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirements Able to work independently with business partners to understand requirements quickly, perform analysis and lead the design review sessions Highly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the business Places the user in the centre of decision making Teams up and collaborates for speed, agility, and innovation Experience with and embraces agile methodologies Strong negotiation and decision-making skill Experience managing and working with globally distributed teams

Employement Category:

Employement Type: Full time
Industry: Food Processing
Role Category: General / Other Software
Functional Area: Not Applicable
Role/Responsibilies: Data Science Analyst

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Keyskills:   Machine Learning Artificial Intelligence DevOps Data Science SQL ADF Spark Hive Pig GitHub Exploratory data Analysis Analytical Skills Communication Skills Agile Methodologies Negotiation Skills Team Management Cloud Azure Databricks CICD ML Ops MLFlow Kubeflow Problemsolving Skills Decisionmaking Skills