Data Scientist

Role Overview

We are seeking an experienced Data Scientist to analyze complex datasets, develop predictive models, and generate actionable business insights. The ideal candidate will have strong expertise in Python, SQL, machine learning, statistics, and data visualization.

Responsibilities

• Analyze large and complex datasets to identify trends, patterns, and business opportunities.
• Develop, train, and deploy machine learning and predictive models.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis.
• Build statistical models and apply advanced analytical techniques.
• Collaborate with business, engineering, product, and analytics teams to define data-driven solutions.
• Develop and optimize ML algorithms for classification, regression, clustering, forecasting, and recommendation use cases.
• Create dashboards and visualizations to communicate insights to stakeholders.
• Evaluate model performance and continuously improve accuracy and scalability.
• Work with data engineers to develop reliable data pipelines and analytical datasets.
• Document models, methodologies, experiments, and analytical findings.
• Stay current with emerging AI, machine learning, and data science technologies.

Requirements

• 3+ years of experience in Data Science, Machine Learning, or Advanced Analytics.
• Strong programming skills in Python.
• Strong SQL skills and experience working with relational databases.
• Solid understanding of statistics, probability, and machine learning concepts.
• Hands-on experience with Scikit-learn, Pandas, NumPy, and related Python libraries.
• Experience with machine learning algorithms including regression, classification, clustering, and time-series forecasting.
• Experience with data visualization tools such as Tableau, Power BI, Matplotlib, or Seaborn.
• Strong experience with data cleaning, feature engineering, and model evaluation.
• Excellent analytical and problem-solving skills.

Skills

• Python
• SQL
• Scikit-learn
• Pandas
• Machine Learning

Nice to Have

• Experience with Generative AI, NLP, Deep Learning, or Computer Vision.
• Knowledge of TensorFlow, PyTorch, or Keras.
• Experience with AWS, Azure, or Google Cloud.
• Familiarity with Spark, Databricks, MLflow, or Airflow.
• Experience deploying ML models using APIs, Docker, Kubernetes, or cloud ML platforms.
• Knowledge of MLOps and model monitoring.
• Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field is preferred.