Data Scientist

We are seeking a skilled and analytical Data Scientist to join our BankSoft Development team. The ideal candidate will be responsible for analyzing large and complex datasets, developing predictive models, and implementing machine learning algorithms to enhance banking products and business decision-making. Key Responsibilities Develop, train, and optimize machine learning models for predictive analytics. Perform data mining, statistical analysis, and exploratory data analysis on structured and unstructured datasets. Build scalable AI and machine learning solutions for banking and financial applications. Design and implement fraud detection, credit scoring, and recommendation systems. Collect, process, clean, and validate data to ensure quality and accuracy. Integrate internal and external data sources to improve analytical capabilities. Create automated anomaly detection systems and continuously monitor their performance. Design algorithms to solve business challenges in the banking and financial services domain. Present analytical findings and business insights through reports and dashboards. Collaborate with software developers, business analysts, and product teams to integrate AI solutions into BankSoft products. Required Skills && Qualifications Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or a related field. 34 years of experience in Data Science or Machine Learning. Strong knowledge of machine learning algorithms such as: o Decision Trees && Random Forests o Support Vector Machines (SVM) o Nave Bayes o K-Nearest Neighbors (K-NN) o Clustering and Classification techniques Proficiency in Python and data science libraries such as: o NumPy o Pandas o Scikit-learn o TensorFlow or PyTorch (preferred) Experience with SQL and relational databases. Knowledge of NoSQL databases such as MongoDB or Cassandra. Strong understanding of statistics, regression analysis, probability distributions, and hypothesis testing. Experience with data visualization tools such as Power BI, Tableau, Microsoft SSRS, or Matplotlib. Knowledge of AI concepts including predictive analytics and recommendation engines. Good programming and scripting skills. Strong analytical and problem-solving abilities. Excellent communication and presentation skills. Preferred Skills Experience in Banking, Financial Services, or FinTech. Knowledge of credit risk modelling, fraud analytics, or customer behaviour analysis. Familiarity with cloud platforms such as AWS, Azure, or Google Cloud is an added advantage. Understanding of MLOps and model deployment is desirable.