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Data Scientist

Wise Equation Solutions Inc.Newark, NJ🇺🇸United StatesPosted 16 Jul 2026

Quick Overview

Work Type
Hybrid
Level
Mid Senior

Job Description

Role Overview

We are looking for a skilled Data Scientist to join our team. You will work on large-scale datasets, build and deploy predictive models, and contribute to data engineering activities. The ideal candidate has a strong foundation in mathematics and statistics, hands-on experience with distributed computing, and the ability to communicate insights to non-technical stakeholders.

 

Must-Have Requirements

  • 3–5+ years of experience as a Data Scientist or similar role
  • Strong hands-on experience with Apache Spark and/or Hadoop for large-scale data processing
  • Proficiency in Python and/or R for data science and ML development
  • Experience building and deploying predictive models (regression, classification, clustering, time-series)
  • Solid understanding of statistics and mathematics (linear algebra, probability, hypothesis testing)
  • Experience with ML frameworks — Scikit-learn, XGBoost, TensorFlow, or PyTorch
  • Experience building/maintaining data pipelines (Airflow, Kafka, dbt, or similar)
  • Ability to explain model behavior and results to non-technical audiences

 

Nice-to-Have Skills

  • Experience with cloud platforms — AWS, Azure, or Google Cloud Platform
  • Familiarity with MLflow or similar model lifecycle management tools
  • Experience with Scala for Spark development
  • Data visualization tools — Tableau, Power BI, or Matplotlib/Seaborn
  • Exposure to NLP or deep learning use cases

 

Education

  • Bachelor''s degree in Computer Science, Statistics, Mathematics, or related field (required)
  • Master''s or PhD preferred

 

Key Responsibilities

  • Process and analyze large datasets using Hadoop/Spark distributed computing frameworks
  • Design, build, and validate machine learning models to solve business problems
  • Translate complex model outputs into actionable insights for business stakeholders
  • Build and maintain scalable data pipelines to support ML workflows
  • Collaborate with data engineers, analysts, and business teams
  • Monitor and improve model performance post-deployment

Skills

Scala
AWS
Linear
MLflow
Machine Learning
NLP
Scikit-learn
Tableau
Airflow
Apache
Apache Spark
Azure
Deep Learning
Google Cloud
Hadoop
Kafka
Power BI
PyTorch
Python
TensorFlow
dbt

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