Potential candidates should have excellent depth and breadth of knowledge in machine learning, data mining, and statistical modeling. They should possess the ability to translate a business problem into an analytical problem, identify the relevant data sets needed for addressing the analytical problem, recommend, implement, and validate the best suited analytical algorithm(s), and generate/deliver insights to stakeholders. Candidates are expected to regularly refer to research papers and be at the cutting-edge with respect to algorithms, tools, and techniques. The role is that of an individual contributor; however, the candidate is expected to work in project teams of 2 to 3 people and interact with Business partners on regular basis. 

Key Roles and Responsibilities of Position:

• Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making
• Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data-driven decision-making
• Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends
• Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation
• Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Minimum Qualifications

• Bachelor’s degree in computer science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. 
• 2+ years of hands-on experience in Python programming for data analysis, machine learning, and with libraries such as NumPy, Pandas, Matplotlib, Plotly, Scikit-learn, TensorFlow, PyTorch, NLTK, spaCy, and Gensim.
• 2+ years of experience with both supervised and unsupervised machine learning techniques.
• 2+ years of experience with data analysis and visualization using Python packages such as Pandas, NumPy, Matplotlib, Seaborn, or data visualization tools like Dash or QlikSense.
• 1+ years' experience in SQL programming language and relational databases.
• Create visualizations to connect disparate data, find patterns and tell engaging stories. This includes both scientific visualization as well as geographic using software such as Power BI.

Preferred Qualifications

•  An MS/PhD in Computer Science, Operational research, Statistics, Applied mathematics, or in any other engineering discipline. PhD strongly preferred.
• Experience working with Google Cloud Platform (GCP) services, leveraging its capabilities for ML model development and deployment.
• Experience with Git and GitHub for version control and collaboration.
• Besides Python, familiarity with one more additional programming language (e.g., C/C++/Java) 
• Strong background and understanding of mathematical concepts relating to probabilistic models, conditional probability, numerical methods, linear algebra, neural network under the hood detail.
• Experience working with large language models such GPT-4, Google, Palm, Llama-2, etc.
• Excellent problem solving, communication, and data presentation skills.