Data Scientist

Experience - 2+ Years
Location - United States, United Kingdom
0–2 years - $75,000–$105,000
2–4 years - $95,000–$130,000
4–6 years - $115,000–$155,000

We are looking for a skilled and analytical Data Scientist with 2+ years of experience in data analysis, statistical modeling, machine learning, and predictive analytics. The ideal candidate will be responsible for collecting, processing, analyzing, and interpreting large datasets to generate actionable business insights and support data-driven decision-making.

The candidate should have strong programming skills in Python and SQL, experience with machine learning algorithms, and the ability to communicate complex analytical findings to technical and non-technical stakeholders.

Key Responsibilities

1. Collect, clean, transform, and analyze structured and unstructured datasets from multiple sources.
2. Develop and implement machine learning models for classification, regression, clustering, and forecasting.
3. Perform exploratory data analysis (EDA) to identify trends, patterns, correlations, and business opportunities.
4. Build predictive and statistical models to solve real-world business problems.
5. Develop data pipelines and automate data preprocessing and model evaluation workflows.
6. Use Python, SQL, and statistical techniques to extract meaningful insights.
7. Perform feature engineering, feature selection, and model optimization.
8. Evaluate machine learning models using metrics such as accuracy, precision, recall, F1-score, and RMSE.
9. Create dashboards and visualizations using Tableau, Power BI, or Python libraries.
10. Collaborate with data engineers, business analysts, product managers, and cross-functional teams.
11. Present analytical findings and recommendations to business stakeholders.
12. Monitor model performance and support model deployment and maintenance.

Required Technical Skills

Skill Category	Technologies
Programming	Python, SQL, R
Python Libraries	Pandas, NumPy, Scikit-learn, SciPy
Machine Learning	Regression, Classification, Clustering, Random Forest, XGBoost
Deep Learning	TensorFlow, PyTorch (basic knowledge)
Statistics	Hypothesis Testing, Probability, A/B Testing
Data Visualization	Tableau, Power BI, Matplotlib, Seaborn
Databases	MySQL, PostgreSQL, SQL Server
Cloud Platforms	AWS, Azure, Google Cloud
Big Data	Spark, PySpark (preferred)
Version Control	Git, GitHub
Deployment	Flask, FastAPI, Docker (preferred)

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related field.
• 2+ years of professional experience in Data Science, Data Analytics, or Machine Learning.
• Strong proficiency in Python and SQL.
• Hands-on experience with machine learning algorithms and statistical modeling.
• Experience working with large datasets and performing exploratory data analysis.
• Strong understanding of data preprocessing, feature engineering, and model evaluation.
• Ability to communicate technical findings effectively.
• Strong analytical, problem-solving, and critical-thinking skills.

Preferred Qualifications

• Experience building and deploying machine learning models in production.
• Familiarity with cloud-based data science environments such as AWS SageMaker or Azure Machine Learning.
• Experience with Generative AI, NLP, or Large Language Models (LLMs).
• Knowledge of MLOps, model monitoring, and CI/CD pipelines.
• Experience working in Agile/Scrum environments.