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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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