Only local and W2, No C2C

Position Description:
Employees in this job function are responsible for predicting and/ or extracting meaningful trends/ patterns/ recommendations from raw data, leveraging data science methodologies including Machine Learning (ML), predictive modeling, math, statistics, advanced analytics, etc. Key Responsibilities: 1) Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making 2) Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making 3) Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends 4) Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation 5) Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness
Skills Required:
Data Mining, Data/Analytics dashboards, ALGORITHMS, Data/Analytics, Data Analysis, Data Science
Experience Required:
Specialist Exp: 5+ experience in relevant field
Education Required:
Master's Degree
Education Preferred:
Doctorate
Additional Information:
Hybrid Position 4 days onsite • Undertake statistical modeling, predictive analytics, and insight generation for the RAV platform • Perform deep dive analyses on RAV vehicles to detect early indicators and recommend actions to prevent/mitigate RAV • Execute quick turn studies for urgent business questions by mining, managing, and exploring large, high dimensional structured and unstructured datasets (e.g., RAV, quality, repair orders, repeat visits, parts orders/supply, service, warranty claims, recalls) • Visualize validation results, analyses, and predictions using Power BI to deliver clear qualitative and quantitative insights • Collaborate closely with architects, project managers, data engineers, software engineers, and other data scientists to test pipelines, validate outputs, and launch new platform capabilities and insights into production for maximum business value • Communicate, present, and interpret analytical results to non technical audiences, cross functional teams, and leadership on a regular basis

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