Job Description - Jr. Data Scientist
Experience:0-1 year |Employment Type:Full-time
Overview
We are looking for a motivated Data Scientist with foundational data science expertise. This position is ideal for recent graduates or early-career professionals eager to work with real-world data, applying both standard and advanced preprocessing and modeling techniques in a collaborative environment.
PLEASE NOTE:
- Mandatory: Email your CV to [Confidential Information] with the subject line: Job ID 202507-DS01:
- This is afull-time role with a hybrid work model
- Students currently pursuing a degree should not apply
- A strong foundation and clear understanding of data science concepts is essential
Key Responsibilities
1. Data Ingestion & Preparation
- Extract and manipulate data using SQL and Python (pandas)
- Import and clean both structured & unstructured datasets
2. Data Preprocessing & Feature Engineering
- Handle missing values, outliers, and duplicates using statistical and ML techniques
- Apply noise reduction, data integration, and transformation (e.g., scaling, encoding)
- Perform dimensionality reduction (e.g., PCA) and ensure quality through data validation
3. Model Building & Evaluation
- Develop machine learning models (e.g., Linear Regression, Random Forest, XGBoost, ARIMA, LSTM) for varied problem types
- Tune hyperparameters using cross-validation and assess models using standard metrics (accuracy, RMSE, F1-score, etc.)
4. Visualization & Insight Generation
- Build dashboards and visualizations using tools like Matplotlib, Seaborn, Plotly, or Tableau
- Conduct statistical analysis to derive actionable business insights and present findings clearly
5. Team Collaboration
- Work closely with cross-functional teams (data engineers, analysts, business units) to align deliverables with organizational goals
- Participate in agile discussions and contribute to iterative development
Required Skills
- Bachelors or Masters in Data Science, Computer Science, Statistics, or related field
- Proficiency in Python or R
- Strong SQL skills for data extraction/manipulation from relational databases
- Experience handling CSV/Excel data ingestion; advanced data cleaning techniques
- Understanding and implementation of various machine learning models (e.g., Linear Regression, Decision Tree, Random Forest, XGBoost, ARIMA, LSTM, SVM, K-Means) and their practical applications
- Ability to evaluate model performance using appropriate metrics: accuracy, precision, recall, F1-score, RMSE, MAE, ROC-AUC, etc
- Experience with feature scaling and categorical variable encoding
- Data visualization using Matplotlib, Seaborn, Plotly, or Tableau
- Analytical thinking, problem-solving, teamwork, and clear communication
Ready to make an impact by transforming data into meaningful insights Apply now!
