Investment Analytics

Job description

Role Summary • Build predictive machine learning models for treasury, cash flow forecasting, and investment recommendations. • Analyze large-scale financial and macroeconomic datasets to generate actionable business insights. • Develop AI-driven analytics solutions for financial products and wealth management. • Collaborate with Product, Engineering, and Business teams to deliver scalable data-driven solutions. Key Responsibilities • Design and deploy predictive ML models for treasury and cash flow forecasting. • Build time-series forecasting models using statistical and machine learning techniques. • Perform exploratory data analysis (EDA), feature engineering, and hypothesis testing. • Develop data pipelines to ingest, clean, and analyze financial and macroeconomic data. • Build investment recommendation models, financial risk scoring, and anomaly detection systems. • Evaluate, optimize, and monitor model performance using appropriate validation techniques. • Create dashboards and visualizations to communicate insights to stakeholders. • Continuously improve models based on changing market conditions and new data. Requirements • Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Economics, or a related quantitative field. • 3–6 years of experience in Data Science, Machine Learning, Advanced Analytics, or Quantitative Modeling. • Strong programming skills in Python. • Experience with time-series forecasting techniques (ARIMA, Prophet, LSTM, Transformer models). • Strong knowledge of statistics, probability, regression, classification, clustering, and optimization. • Experience working with financial, transactional, or time-series datasets. • Familiarity with Git and collaborative development workflows. • Excellent analytical, problem-solving, and communication skills. Preferred Qualifications • Experience in financial markets, treasury, banking, investment research, or fintech. • Knowledge of macroeconomics, financial modeling, and quantitative finance. • CFA (completed) is an added advantage. Skills: models,forecasting,treasury,cash flow,investment,wealth,datasets