21d ago

Data Scientist - R01571773

India·PuneEmployeemid

Data ScientistData

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Quick Summary

Key Responsibilities

Design, develop, and deploy advanced statistical and machine learning models using Python, R, and specialized frameworks to address complex business challenges Conduct rigorous statistical analysis,

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Data ScientistData

Data Scientist

Experience Range: With at least 4 years of experience in advanced data science, statistical analysis, and machine learning model development, including hands-on work with large datasets and production model deployment. Key Responsibilities:

Design, develop, and deploy advanced statistical and machine learning models using Python, R, and specialized frameworks to address complex business challenges

Conduct rigorous statistical analysis, including hypothesis testing, regression analysis, and probabilistic modeling, to extract actionable insights from large-scale data

Implement and validate data quality checks using tools such as Great Expectations and Evidently AI to ensure data and model integrity

Collaborate with cross-functional teams to define data-driven strategies, translate business requirements into analytical solutions, and present findings to stakeholders

Develop, optimize, and maintain forecasting models using techniques such as exponential smoothing, ARIMA, and ARIMAX to support business planning

Build, train, and evaluate classification and regression models using ML frameworks (TensorFlow, PyTorch, Sci-Kit Learn, Keras, MXNet, CNTK)

Deploy and monitor models in production environments using scalable cloud-native tools such as KubeFlow and BentoML

Document methodologies and contribute to continuous improvement of analytics best practices

Required Skills:

Advanced proficiency in Python and PySpark for data analysis and model development

Expertise in statistical analysis and computing using SAS or SPSS

Hands-on experience with regression techniques including linear and logistic regression

Strong knowledge of hypothesis testing, including T-Test and Z-Test methodologies

Proficient in building and interpreting probabilistic graphical models

Experience with classification algorithms such as Decision Trees and Support Vector Machines (SVM)

Skilled in forecasting techniques including exponential smoothing, ARIMA, and ARIMAX

Familiarity with distance metrics such as Hamming, Euclidean, and Manhattan Distance

Working knowledge of R and R Studio for statistical modeling

Experience with data validation and monitoring tools such as Great Expectations and Evidently AI

Preferred Skills:

Experience deploying machine learning models using KubeFlow or BentoML

Proficiency with deep learning frameworks such as TensorFlow, PyTorch, Keras, MXNet, or CNTK

Background in cloud-based analytics platforms (e.g., AWS SageMaker, Azure ML, Google AI Platform)

Exposure to automated machine learning (AutoML) workflows

Desired Qualifications:

Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline

Certification in Data Science or Machine Learning from a recognized provider (e.g., Microsoft Certified: Azure Data Scientist Associate, IBM Data Science Professional Certificate)