Data Scientist

Data Scientist Permanent Position! Job Summary: As a Data Scientist, the beneficiary’s job duties will include: ● Use statistical techniques such as A/B testing to analyze and improve client onboarding applications, helping enhance user experience and drive better conversion outcomes. ● Design and implement data pipelines, data preparation frameworks, and analytical models to analyze large datasets using statistical tools. ● Perform data analysis, feature engineering, and model development for predictive analytics using python programming language. ● Develop and optimize machine learning models for financial data use cases such as forecasting and anomaly detection. ● Evaluate machine learning models using performance metrics to ensure they deliver reliable and meaningful results. ● Analyze business or financial data through reporting software to support decision-making. ● Create dashboards and analytical reports using Microsoft Power BI to support business decision-making. ● Collaborate with stakeholders to translate requirements into scalable AI/ML solutions and present insights. ● Build and deploy AI-powered applications using agentic workflows leveraging OpenAI models and related frameworks. The technical skills required for this role are: working knowledge of data science methodologies, statistical analysis, machine learning algorithms, A/B testing, data pipelines, proficiency in programming languages such as Python and SQL, cross-functional collaboration, AI/ML system design, large language models, agentic workflows, cloud platforms such as Azure and Databricks, and dashboarding/visualization tools like Microsoft Power BI. Minimum Requirements: • Bachelor’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a closely related field. • Related experience in Data Science, Machine Learning, Statistical Analysis, Predictive Modeling, and Data Analytics. • Strong experience working with Python, R, SQL, Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch, or similar data science and machine learning frameworks. • Experience with data visualization and reporting tools such as Tableau, Power BI, Matplotlib, or Seaborn. • Strong knowledge of statistical analysis, hypothesis testing, data mining, feature engineering, and model evaluation techniques. • Experience processing and analyzing large structured and unstructured datasets from multiple data sources. • Experience with cloud platforms such as Amazon Web Services (AWS), Microsoft Azure, or Google Cloud Platform (GCP) is preferred. • Knowledge of data preprocessing, ETL workflows, data validation, and data quality management practices. • Understanding of Machine Learning operations (MLOps), model deployment, monitoring, and CI/CD pipelines is preferred. • Familiarity with Big Data technologies such as Apache Spark, Hadoop, Databricks, or Snowflake is preferred. • Understanding of data governance, data privacy, security standards, and role-based access controls. • Strong analytical, problem-solving, organizational, communication, presentation, and teamwork skills.