Data Scientist

Job Title: Data Scientist 

Location: New Jersey (Hybrid / On-site)

Type of Employment: Full-time

About the Role:

We are seeking an experienced Data Scientist with 5–7 years of hands-on experience in building predictive models, analyzing large datasets, and developing advanced algorithms. The ideal candidate is highly proficient in Python, Machine Learning, Statistics, and Deep Learning, with strong analytical thinking and problem-solving skills. You will work with cross-functional teams to deliver data-driven insights and scalable ML solutions that support business strategy and innovation.

Key Responsibilities:

• Develop, train, and optimize Machine Learning and Deep Learning models for forecasting, classification, recommendation, NLP, and other predictive use cases.
• Apply statistical modeling, hypothesis testing, and experimental design to solve complex business problems.
• Design and implement algorithms to uncover patterns, trends, and insights from structured and unstructured datasets.
• Perform data wrangling, cleaning, feature engineering, and exploratory data analysis (EDA).
• Build end-to-end data science workflows: data preparation → modeling → validation → deployment.
• Collaborate with data engineers and product teams to integrate models into production environments.
• Use Python libraries such as NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch, Statsmodels, etc.
• Communicate insights clearly via reports, dashboards, presentations, and visualizations.
• Monitor model performance and update models to account for drift or changes in data patterns.
• Stay current with advances in AI/ML, deep learning, and statistical methodologies.

Required Qualifications:

• 5–7 years of experience as a Data Scientist, ML Engineer, or similar role.
• Strong proficiency in Python and ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.).
• Deep understanding of Machine Learning algorithms, supervised & unsupervised learning.
• Strong background in Statistics, probability, hypothesis testing, regression, and statistical modeling.
• Hands-on experience with Deep Learning architectures (CNNs, RNNs, Transformers).
• Experience working with large datasets, data preprocessing, and feature engineering.
• Solid understanding of model evaluation, tuning, cross-validation, and performance metrics.
• Ability to translate business problems into analytic approaches and actionable insights.
• Experience with SQL and exposure to cloud platforms (AWS/Azure/Google Cloud Platform).
• Strong communication, problem-solving, and collaboration skills.

Preferred Skills:

• Experience with NLP, LLMs, time-series forecasting, or anomaly detection.
• Familiarity with MLOps tools such as MLflow, SageMaker, Azure ML, or Vertex AI.
• Experience deploying models using APIs, microservices, or containerized environments.
• Knowledge of big data tools (Spark, Databricks, Hadoop) is a plus.
• Visualization experience with tools like Power BI, Tableau, or Plotly