Description

You will use statistical modeling and machine learning to extract insights from complex datasets and drive decision-making.

Responsibilities

• Collect, clean, and preprocess large datasets from multiple sources.
• Perform exploratory data analysis to identify patterns and trends.
• Develop, implement, and validate statistical models and algorithms.
• Design, train, and deploy machine learning models to automate processes and predict outcomes.
• Collaborate with data engineers and analysts to translate business requirements into technical solutions.

Required Skills

• 6+ years of academic and relevant industry experience.
• Proficiency in Python and SQL.
• Experience with data manipulation and analysis libraries including Pandas, NumPy, and Scikit-learn.
• Hands-on experience with Databricks for big data processing and analytics.
• Strong analytical skills to identify trends and draw actionable conclusions from complex data.
• Ability to communicate technical information clearly to non-technical stakeholders.
• Bachelor's, Master's, or PhD degree in a quantitative field such as CS, Machine Learning, Mathematics, or Statistics.
• Experience with data visualization tools like Matplotlib, Seaborn, or D3.js.
• Familiarity with Hadoop and Spark.

Preferred Skills

• Proficiency with the Elastic Stack (Elasticsearch and Kibana).
• Experience with cloud platforms including AWS, Azure, or Google Cloud.
• Knowledge of advanced machine learning techniques like deep learning or NLP.

Key Skills

Education

Bachelor's, Master's or PhD degree