Senior Data Scientist: ML & Data Quality (Remote)

Carnation Infotech; United States; Remote; USD 130,000 - 160,000; Full time

Job summary

Carnation Infotech seeks a Data Scientist to join the team and develop advanced analytics, forecasting, anomaly detection, entity resolution, and data intelligence solutions for an enterprise data platform.

The ideal candidate will possess strong hands-on experience in statistical analysis, machine learning, Python, SQL, data profiling, predictive modelling, and business problem solving, collaborating with business and technical teams to drive insights and data quality.

Qualifications

• 10+ years of data science, analytics, or statistical modelling.
• Hands-on experience with Python, pandas, NumPy, scikit-learn, and Jupyter notebooks.
• Strong SQL and data wrangling skills to extract and validate data.

Responsibilities

• Analyze large-scale datasets including POS, sales, customer, product, and finance data.
• Perform data profiling to identify missing values, duplicates, outliers, and quality gaps.
• Develop ML models for entity resolution, anomaly detection, segmentation, and forecasting.
• Design POS file similarity cohorting models and reusable ingestion/mapping templates.
• Build Named Entity Resolution to standardize names against master data.
• Create data quality scoring frameworks and dataset health metrics.
• Develop sales and demand forecasting models using statistical and ensemble methods.
• Monitor model performance and data drift; document methodology and assumptions.

Skills

Python

Pandas/NumPy

ML algorithms

Statistical analysis

Data profiling

Business problem solving

Communication

Tools

SQL

Power BI

Tableau

Azure Databricks

Spark

XGBoost

Job description

Carnation Infotech seeks a Data Scientist to join the team and develop advanced analytics, forecasting, anomaly detection, entity resolution, and data intelligence solutions for an enterprise data platform.

The ideal candidate will possess strong hands-on experience in statistical analysis, machine learning, Python, SQL, data profiling, predictive modelling, and business problem solving, collaborating with business and technical teams to drive insights and data quality.