Job Summary

We are seeking a highly motivated Predictive Analytics Scientist to develop advanced analytical models and AI-driven solutions that support strategic business decisions. The ideal candidate will leverage statistical modeling, machine learning, data mining, and predictive analytics techniques to identify trends, forecast outcomes, and generate actionable insights from large and complex datasets.

Key Responsibilities

• Design, develop, and deploy predictive models using machine learning and statistical techniques.
• Analyze structured and unstructured data to identify patterns, trends, and business opportunities.
• Build forecasting models for customer behavior, sales, demand planning, risk assessment, and operational efficiency.
• Collaborate with cross-functional teams to understand business requirements and translate them into analytical solutions.
• Develop and maintain data pipelines, feature engineering processes, and model monitoring frameworks.
• Evaluate model performance and continuously improve prediction accuracy.
• Present findings, recommendations, and insights to technical and non-technical stakeholders.
• Conduct A/B testing and experimental analysis to measure business impact.
• Stay current with advancements in AI, machine learning, and predictive analytics technologies.

Required Qualifications

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.
• 3+ years of experience in predictive analytics, machine learning, or data science.
• Strong knowledge of statistical modeling, forecasting, regression, classification, clustering, and optimization techniques.
• Proficiency in Python, R, SQL, and data visualization tools.
• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
• Strong analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with Generative AI, Large Language Models (LLMs), and AI-powered analytics solutions.
• Knowledge of cloud platforms such as AWS, Azure, or Google Cloud.
• Experience working with big data technologies including Spark, Hadoop, or Databricks.
• Familiarity with MLOps, model deployment, and monitoring practices.

Technical Skills

• Predictive Modeling
• Machine Learning
• Statistical Analysis
• Time Series Forecasting
• Data Mining
• Python, R, SQL
• Tableau, Power BI
• AI & Generative AI
• Cloud Computing
• MLOps

Success Metrics

• Improved forecasting accuracy and business performance.
• Increased efficiency through data-driven decision-making.
• Successful deployment and adoption of predictive models.
• Delivery of actionable insights that generate measurable business value.