Data Scientist Traditional ML Position Available In Hudson, New Jersey

Data Scientist –

Traditional ML Nova Web Technologies Jersey City, NJ Job Details Estimated:

$78.1K – $120K a year 11 hours ago Qualifications TensorFlow Power BI 6 years Computer Science Applied Mathematics Hypothesis testing PyTorch Big data Spark NumPy Tableau Master’s degree SQL Pandas AWS Bachelor’s degree Machine learning Feature extraction Regression analysis Predictive analytics Financial services Data science Data visualization Clustering Senior level AI Communication skills

Python Full Job Description Location:

Jersey City /

Remote Type:

Contract Experience Required:

6 +

Years Position Overview:

We are seeking an experienced Data Scientist with deep expertise in traditional machine learning approaches to join our analytics team. The ideal candidate will have strong hands-on experience across the full lifecycle of predictive model development—from data preprocessing and exploratory data analysis (EDA) to model building and evaluation.

Key Responsibilities:

Lead the end-to-end ML model lifecycle : data collection, preprocessing, exploratory data analysis (EDA), feature engineering, model development, evaluation, and deployment. Develop and optimize classification models (Logistic Regression, Decision Tree, Random Forest) for targeted business use cases. Build high-performing regression models (Linear Regression, Gradient Boosting, Neural Networks, K-Nearest Neighbors) to support quantitative decision-making. Apply unsupervised learning methods (K-means and other clustering approaches) to identify patterns, segment data, and detect anomalies. Collaborate with stakeholders to translate business challenges into data science initiatives. Evaluate model performance using appropriate metrics and iterate rapidly. Communicate findings and insights clearly to technical and non-technical audiences. Document methodologies and maintain best practices to ensure reproducibility and knowledge sharing. Must –

Have Qualifications:

Bachelor’s degree in Computer Science, Statistics, Applied Mathematics, or a related field; Master’s preferred. 6-10 years of hands-on experience in machine learning with focus on predictive modeling. Proven expertise in building and deploying:

Classification :

Logistic Regression, Decision Trees, Random Forests Regression :

Linear Regression, Gradient Boosting, Neural Networks, KNN Unsupervised Learning :

K-means and other clustering techniques. Proficiency in Python and libraries like NumPy, pandas, scikit-learn, with familiarity in TensorFlow or PyTorch. Strong foundation in statistical modeling, hypothesis testing, and performance metrics. Experience with SQL and big data frameworks (e.g., Spark) is a plus. Excellent communication skills and ability to translate technical results into business impact. Familiarity with data visualization tools (Tableau, Power BI) is preferred.

Preferred Qualifications:

Prior experience in insurance or financial services domains. Exposure to cloud ML platforms like AWS SageMaker, Azure ML, or Google AI Platform. Awareness of MLOps best practices , including monitoring, version control, and deployment pipelines.

Application Process:

Qualified candidates should submit their resume, cover letter, and a brief description of relevant projects they’ve led.