Jr. Data Scientist

Experience:

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 careers@solvusai.com with the subject line:

  “Job ID 202507-DS01: <Your Name>”

• This is a
  full-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!