Senior Data Scientist

As an Associate Manager - Senior Data Scientist at our company, you will have the opportunity to tackle some of the most significant business challenges faced by our clients by leveraging a variety of AI and ML technologies. Your role will involve close collaboration with business partners and subject matter experts to conceptualize and implement innovative solutions leveraging data to achieve predefined objectives. Engaging with clients to gain a deep understanding of their current and future business objectives and translating these into analytical frameworks will be a key aspect of your responsibilities. You will be tasked with developing customized models based on a thorough comprehension of the underlying data, data structures, and business challenges to ensure that the deliverables align with the specific needs of the clients. Creating models that are repeatable, interpretable, and scalable will also be a crucial part of your role. Effective communication of the analytics approach and insights to a broader business audience will be essential. Additionally, collaborating with team members, peers, and leadership both within our organization and at client companies will be pivotal for success in this role. To qualify for this position, you should possess a Bachelor's or Master's degree in a quantitative field such as CS, machine learning, mathematics, or statistics, or have equivalent experience. You should have at least 5 years of experience in data science with a focus on building hands-on ML models. Your expertise should extend to working with LMs such as Llama, T5, Falcon, Langchain, or similar frameworks, and you should have a comprehensive understanding of the evolution of NLP from Traditional Language Models to Modern Large Language Models. Familiarity with concepts such as LORA, RAG, Instruct fine-tuning, and Quantization is also required. Experience in leading the complete lifecycle of predictive modeling solutions, proficiency in Python programming with knowledge of numerical, data analysis, and AI frameworks like NumPy, Pandas, Scikit-learn, and Jupyter, as well as advanced SQL skills with exposure to SQL Server and Spark is crucial. Knowledge of predictive/prescriptive analytics, machine learning algorithms (Supervised and Unsupervised), deep learning algorithms, and Artificial Neural Networks is necessary. Moreover, experience in Natural Language Processing (NLTK) and text analytics for tasks such as information extraction, parsing, and topic modeling is preferred. Strong verbal and written communication skills, excellent troubleshooting and problem-solving abilities, and the ability to thrive in a dynamic and innovative environment are essential attributes for this role. Familiarity with data visualization tools like PowerBI, Tableau, R Shiny, and experience with cloud platforms such as Azure and AWS are advantageous but not mandatory.,