Data Science Analyst
2 weeks ago
Main Purpose:
The Data Science 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.You will be part of a collaborative interdisciplinary team around data, where you will be responsible of our continuous delivery of statistical/ML models.
You will work closely with process owners, product owners and final business users. This will provide you the correct visibility and understanding of criticality of your developments.Please note that this role will be based ONLY in India. The role does not involve any movement to other PepsiCo offices outside India in future.
Responsibilities
Delivery of key Advanced Analytics/Data Science projects within time and budget, particularly around DevOps/MLOps and Machine Learning models in scopeCollaborate with data engineers and ML engineers to understand data and models and leverage various advanced analytics capabilitiesEnsure on time and on budget delivery which satisfies project requirements, while adhering to enterprise architecture standardsUse 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 PipelinesSetup cloud alerts, monitors, dashboards, and logging and troubleshoot machine learning infrastructureAutomate ML models deploymentsQualifications
Minimum 4+ year of SQL experienceMinimum 2+ years of Python and Pyspark experienceExperience in DevOps and 2+ yrs in Machine Learning (ML) with hands-on experience with one or more cloud service providers AWS, GCP, (Azure preferred) is preferredBE/ in Computer Science, Maths, technical fields
Stakeholder engagement-BU, VendorsSkills, Abilities, Knowledge:
Data Science – Hands on experience and strong knowledge of building machine learning models – supervised and unsupervised models.
Knowledge of Time series/Demand Forecast models is a plusProgramming Skills – Hands-on experience in statistical programming languages like Python, Pyspark and database query languages like SQLStatistics – Good applied statistical skills, including knowledge of statistical tests, distributions, regression, maximum likelihood estimatorsCloud (Azure) – Experience in Databricks and ADF is desirableFamiliarity with Spark, Hive, Pig is an added advantageModel deployment experience will be a plusExperience with version control systems like GitHub and CI/CD toolsExperience is Exploratory data AnalysisKnowledge of ML Ops / DevOps and deploying ML models is requiredExperience using MLFlow, Kubeflow etc.
will be preferredExperience executing and contributing to ML OPS automation infrastructure is good to haveExceptional analytical and problem-solving skillsExperience building statistical models in the Commercial, Net revenue Management or Supply chain space is a plusDifferentiating Competencies Required:
Ability to work with virtual teams (remote work locations); collaborate with technical resources (employees and contractors) based in multiple locations across geographiesParticipate in technical discussions, driving clarity of complex issues/requirements to build robust solutionsStrong communication skills to meet with business, understand sometimes ambiguous, needs, and translate to clear, aligned requirementsAble to work independently with business partners to understand requirements quickly, perform analysis and lead the design review sessionsHighly influential and having the ability to educate challenging stakeholders on the role of data and its purpose in the businessPlaces the user in the centre of decision makingTeams up and collaborates for speed, agility, and innovationExperience with and embraces agile methodologiesStrong negotiation and decision-making skillExperience managing and working with globally distributed teams
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