Senior Data Scientist: Feature Engineering & ML Pipelines

Danta Technologies; San Antonio (TX); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Healthcare insurance

Paid time off

Major holidays and sick leave

Job summary

Danta Technologies is seeking an experienced Data Scientist to lead feature selection, engineering, and statistical modeling initiatives. You will build scalable feature pipelines, validate features with rigorous statistical methods, and deploy ML models in collaboration with Data Engineering and MLOps teams.

You will work with Python, SQL, and NLP to extract meaningful features from large datasets, driving predictive analytics and business impact across complex data sources.

Qualifications

• 8+ years of experience in Data Science, Analytics, or Machine Learning.
• Strong expertise in Feature Selection, Feature Engineering, Statistical Modeling, and Predictive Modeling.
• Deep understanding of Statistics, Hypothesis Testing, Regression Analysis, Feature Importance Techniques, and Dimensionality Reduction.
• Hands-on experience in Machine Learning model development, validation, tuning, and evaluation.
• Strong proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels).
• Strong SQL skills with experience writing complex queries and performing large-scale data analysis.
• Experience with NLP techniques, text processing, and feature extraction.
• Knowledge of Data Engineering concepts, ETL/ELT pipelines, data transformation, and production data workflows.
• Experience with model deployment, MLOps concepts, and collaboration with Data Engineering teams.
• Excellent analytical, problem-solving, documentation, and stakeholder communication skills.

Responsibilities

• Lead feature selection initiatives using covariance, hypothesis testing, regression, IV, WoE, PCA, and feature importance methods.
• Analyze large datasets to identify key variables influencing outcomes and predictive performance.
• Design, develop, and maintain scalable feature engineering frameworks for structured and unstructured data.
• Conduct EDA, data profiling, and statistical validation to uncover patterns and predictive features.
• Use Python and SQL to extract, transform, and validate data, ensuring data quality.
• Build, train, validate, and optimize ML models to solve business problems and improve accuracy.
• Apply ML algorithms to assess feature effectiveness and model performance.
• Leverage NLP to extract and optimize features from textual data.
• Collaborate with stakeholders to translate requirements into actionable analytical features and models.
• Build and productionize data pipelines and feature datasets with Data Engineering teams.
• Document pipelines, logic, inputs/outputs, and deployment requirements for handover to engineering.
• Support model deployment, monitoring, and continuous improvement with Data Engineering and MLOps teams.
• Document methodologies, findings, and recommendations for reusable analytics solutions.

Skills

Feature Selection

Feature Engineering

Statistical Modeling

Predictive Modeling

Python

SQL

NLP

Data Engineering

ETL/ELT

MLOps

Model Deployment

Collaborate with stakeholders

Tools

Pandas

NumPy

Scikit-learn

Statsmodels

Job description

Danta Technologies is seeking an experienced Data Scientist to lead feature selection, engineering, and statistical modeling initiatives. You will build scalable feature pipelines, validate features with rigorous statistical methods, and deploy ML models in collaboration with Data Engineering and MLOps teams.

You will work with Python, SQL, and NLP to extract meaningful features from large datasets, driving predictive analytics and business impact across complex data sources.