Data Scientist

Overview

Candidate who excels at preparing raw data for analysis and has the expertise to derive actionable features for analytics and machine learning.

Candidate will be involved in the full data lifecycle—from ingestion and cleaning to modeling and feature engineering.

Experience

Key Responsibilities

• Data Collection & Organization

  : Gather raw data from diverse sources and structure it into usable formats.

• Data Cleaning

  : Identify and correct errors, handle missing values, and resolve formatting inconsistencies.

• Data Transformation

  : Reshape and restructure datasets to meet analytical requirements.

• Data Analysis & Modeling

  : Apply statistical and machine learning techniques to analyze data and build predictive models.

• Feature Engineering

  : Design, create, and select meaningful features from raw data to improve model performance and interpretability.

• Experimentation

  : Design and execute experiments to test hypotheses and measure impact.

• Visualization

  : Create compelling visualizations and dashboards to communicate findings. (ex. SHAP, Features, Correlation, etc)

Technical Skills

• Proficiency in

  SQL and Python

  , for data manipulation, analysis, and automation.
• Experience in Databricks, API ingestion
• Experience in Jupyter, DBeaver, SSMS Dev Tools
• Familiarity in Azure Cloud Platform
• Experience with

  machine learning libraries

  (e.g., scikit-learn, etc.).
• Strong knowledge of

  database management systems

  and

  data wrangling tools

  .
• Familiarity with

  feature engineering techniques

  , including encoding, scaling, and dimensionality reduction.

Education & Experience

• Bachelor’s degree in

  Data Science

  ,

  Computer Science

  ,

  Statistics

  , or a related field.
• Prior experience in data wrangling, feature engineering, and data science roles is highly desirable.