Data Scientist

UPS

Chennai District

On-site

INR 1,069,404 - 1,604,106

Full time

14 days+

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Job summary

Une entreprise de logistique internationale cherche un Data Scientist pour créer et mettre en œuvre des modèles analytiques avancés. Le candidat idéal aura une expertise en R, SQL, et Python, avec une expérience en IA et en apprentissage automatique. Ce poste implique la définition de sources de données, le développement de pipelines de données, et la présentation des résultats à divers intervenants. Un Master en mathématiques ou informatique est requis. Rejoignez une organisation axée sur l'égalité des chances.

Qualifications

Expertise en R, SQL, Python et autres langages de haut niveau.
Expérience en analyse de données et développement de modèles analytiques avancés.
Compréhension des pipelines de gestion des données.

Responsibilities

Définir les sources de données clés et livrer des modèles.
Développer et mettre en œuvre des pipelines pour le nettoyage et la transformation des données.
Présenter les résultats analytiques et formuler des recommandations.

Skills

R, SQL, Python

Analyse de données exploratoires

Modélisation avancée

Techniques statistiques

Communication écrite

Education

Master en mathématiques, informatique ou domaine quantitatif équivalent

Tools

VertexAI

Databricks

Sagemaker

PyTorch

Tensorflow

Keras

Job description

Fiche De Poste

DATA SCIENTIST

Job Summary

Avant de postuler à un emploi, sélectionnez votre langue de préférence parmi les options disponibles en haut à droite de cette page. Découvrez votre prochaine opportunité au sein d'une organisation qui compte parmi les 500 plus importantes entreprises mondiales. Envisagez des opportunités innovantes, découvrez notre culture enrichissante et travaillez avec des équipes talentueuses qui vous poussent à vous développer chaque jour. Nous savons ce qu’il faut faire pour diriger UPS vers l'avenir : des personnes passionnées dotées d’une combinaison unique de compétences. Si vous avez les qualités, de la motivation, de l'autonomie ou le leadership pour diriger des équipes, il existe des postes adaptés à vos aspirations et à vos compétences d'aujourd'hui et de demain.

This Data Scientist creates and implements advanced analytics models and solutions to yield predictive and prescriptive insights from large volumes of structured and unstructured data. This position works with a team responsible for the research and implementation of predictive requirements by leveraging industry standard machine learning and data visualization tools to draw insights that empower confident decisions and product creation. This position leverages emerging tools and technologies available in On-prem and Cloud environments. This position utilizes industry standard machine learning and data visualization tools to transform data and analytics requirements into predictive solutions and provide data literacy on a range of machine learning systems at UPS. This position identifies opportunities for driving descriptive to predictive and prescriptive solutions, which become inputs to department and project teams on their decisions supporting projects.

Responsibilities

Defines key data sources from UPS and external sources to deliver models.
Develops and implements pipelines that facilitates data cleansing, data transformations, data enrichments from multiple sources (internal and external) that serve as inputs for data and analytics systems.
For larger teams, works with data engineering teams to validate and test data and model pipelines identified during proof of concepts.
Develops data design based on the exploratory analysis of large amounts of data to discover trends and patterns that meet stated business needs.
Defines model key performance indicator (KPI) expectations and validation, testing, and re-training of existing models to meet business objectives.
Reviews and creates repeatable solutions through written project documentation, process flowcharts, logs, and commented clean code to produce datasets that can be used in analytics and/or predictive modeling.
Synthesizes insights and documents findings through clear and concise presentations and reports to stakeholders.
Presents operationalized analytic findings and provides recommendations.
Incorporates best practices on the use of statistical modeling, machine learning algorithms, distributed computing, cloud-based AI technologies, and run time performance tuning with the goal of deployment and market introduction.
Leverages emerging tools and technologies together with the use of open-source or vendor products in the creation and delivery of insights that support predictive and prescriptive solutions.

Qualifications

Expertise in R, SQL, Python and/or any other high-level languages.
Exploratory data analysis (EDA), data engineering and development of advanced analytics models.
Experience in development of AI and ML using platforms like VertexAI, Databricks or Sagemaker, and familiarity with available frameworks like PyTorch, Tensorflow and Keras.
Experience applying models from small to medium scaled problems.
Strong analytical skills and attention to detail.
Able to engage key business and executive-level stakeholders to translate business problems to a high-level analytics solution approach.
Expertise with statistical techniques, machine learning, and/or operations research and their application in business.
Deep understanding of data management pipelines and experience in launching moderate scale advanced analytics projects in production.
Demonstrated experience in Cloud-AI technologies and knowledge of environments both in Linux/Unix and Windows.
Experience implementing open-source technologies and cloud services; with or without the use of enterprise data science platforms.
Core AI / Machine Learning knowledge and application in supervised and unsupervised learning domains.
Familiarity with Java or C++ is a plus.
Solid oral and written communication skills, especially around analytical concepts and methods.
Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audiences.
Master’s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.