Data Scientist 2

Job Description

We are looking for a Data Scientist with 2+ years of experience in data analysis, statistical modeling, machine learning, and predictive analytics. The ideal candidate will have hands-on experience with Python, SQL, machine learning techniques, and data visualization, and be able to translate business problems into data-driven solutions.

Key Responsibilities

• Analyze large and complex datasets to identify trends, patterns, and actionable insights.
• Develop and implement machine learning models for classification, regression, clustering, forecasting, and prediction.
• Perform data cleaning, preprocessing, feature engineering, and exploratory data analysis (EDA).
• Build, evaluate, tune, and deploy machine learning models using appropriate algorithms.
• Work with business and technical teams to understand requirements and translate them into analytical solutions.
• Develop statistical models and perform hypothesis testing and correlation analysis.
• Use SQL to extract, transform, and validate data from databases.
• Create dashboards and visualizations to communicate insights effectively to stakeholders.
• Monitor model performance and continuously improve model accuracy and reliability.
• Document analytical methodologies, models, assumptions, and results.
• Collaborate with data engineers, BI developers, product managers, and other stakeholders.
• Stay up to date with developments in machine learning, AI, and data science.

Required Skills

• 2+ years of experience in data science, machine learning, or analytics.
• Strong programming skills in Python.
• Hands-on experience with Pandas, NumPy, and scikit-learn.
• Strong SQL skills.
• Good understanding of machine learning algorithms, regression and classification, clustering, feature engineering, model evaluation and validation, exploratory data analysis, statistics, and probability.
• Experience with data visualization tools such as Power BI, Tableau, Matplotlib, or Seaborn.
• Experience working with structured and unstructured datasets.
• Strong analytical and problem-solving skills.

Good to Have

• Experience with TensorFlow or PyTorch.
• Knowledge of NLP, generative AI, or LLMs.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of MLflow or other MLOps tools.
• Experience deploying machine learning models through APIs.
• Knowledge of Spark or PySpark.
• Experience working with large-scale datasets.