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Data Scientist USC

Savi TechnologiesUnited States🇺🇸United StatesPosted 7 Aug 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Location: New York, NY - Remote BUT once in few months, collaboration meetings scheduled, so associate required to attend for a day or two
Duration: 6 months
Data Scientist Competencies: 6-8+ years experience
Digital : Data Science Role Description:
The Data Scientist will be responsible for applying statistical analysis, machine learning, and data mining techniques to solve business problems and generate actionable insights.
The role focuses on structured data analytics, predictive modeling, and business decision support using traditional data science methods. Key Responsibilities
Perform data exploration, cleaning, and preprocessing on structured and semi-structured datasets
Develop and implement statistical models and machine learning algorithms (regression, classification, clustering, time series)
Conduct hypothesis testing and exploratory data analysis (EDA) to identify trends and patterns
Build predictive and forecasting models to support business decisions
Translate business requirements into analytical problems and modeling approaches
Design and execute A/B testing and experimental analysis
Create data visualizations and dashboards to communicate insights clearly
Collaborate with business stakeholders to drive data-driven decision making
Validate model accuracy, performance, and robustness using appropriate metrics
Document methodologies, assumptions, and findings for auditability and reuse Required Skills:
Programming & Tools
Python (must-have)
SQL for data extraction and manipulation
Experience with Jupyter Notebook / similar environments
Statistical & Analytical Skills
Strong foundation in:
o Probability and statistics
o Hypothesis testing
o Regression analysis
o Time series analysis
Experience with classical ML techniques:
o Linear/Logistic Regression
o Decision Trees, Random Forest
o K-Means / clustering methods
Data Handling
Data wrangling and feature engineering
Experience working with datasets (NoSQL, RDBMS, data warehouses)
Familiarity with data quality and validation techniques
Visualization & Reporting
Tools such as Tableau / Power BI / Matplotlib / Seaborn
Ability to present insights in business-friendly language
Preferred Skills
Exposure to ETL processes and basic data engineering concepts
Knowledge of optimization or operations research techniques
Experience working in cross-functional teams

Skills

SQL
ETL
Linear
Machine Learning
Tableau
Jupyter
Power BI
Python

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