AI/ML

Responsibilities

We are seeking a highly skilled and motivated Senior Principal Analyst to join our team. The ideal candidate will
possess a strong technical background with expertise in various programming languages and data technologies, Data
Science and Artificial Intelligence coupled with exceptional business acumen and communication skills. As a Senior
Principal Analyst, you will be responsible for leading technical initiatives, designing innovative solutions, and providing expert consultation to our clients.

Key Responsibilities:

• Develop & implement machine learning models & algorithms to extract insights from large datasets.
• Select features, build, and optimize classifiers/regressors using machine learning and deep learning techniques.
• Process, cleanse, and verify the integrity of data used for analysis.
• Perform data mining and analytics to support continuous risk monitoring and risk assessments.
• Utilize various statistical techniques and predictive modeling to drive and identify indicators of risk.
• Design & maintain effective information and data models that align with the organization’s data requirements and
objectives.
• Translate complex business problems into technical solutions and architectures.
• Develop and present Proof of Concepts (POCs) and technical client presentations.
• Mentor and provide guidance to junior data scientists and analysts.

Technical Skills:

• Advanced proficiency in Python coding for AI/ML algorithms and data analytics.
• Strong grasp of machine learning algorithms: Random Forest, Gradient Boosting, Naive Bayes, SVM, KNN.
• Deep understanding of deep learning techniques: DNN, CNN, RNN, LSTM, Autoencoders.
• Proficiency with ML/AI software and tools: scikit-learn, TensorFlow, PyTorch, CARET.
• Solid understanding of statistical concepts: Sampling Theory, Descriptive Statistics, Probability Distributions,
Statistical Tests, Dimensionality Reduction, Hypothesis Testing, Maximum Likelihood Estimators, and Inference.
• Expertise in model validation, hyperparameter tuning, and model selection techniques: Cross-validation, Bootstrap methods.
• Proficiency in data analytics tools for queries and analyses, and data visualization platforms for summaries,
predictive analyses, comparative analyses, dashboards, and reports.
• Strong command of query languages: SQL and Spark.
• Familiarity with cloud platforms such as AWS and GCP is a plus.

Qualifications:

• Bachelor’s or master’s degree in computer science, Information Technology, Engineering, or a related field.
• Minimum of 10 years of experience in a similar role with recent 8 years of relevant experience.
• Relevant certifications in programming languages, data technologies, or cloud platforms would be advantageous.