Data Scientist, Senior

Develop and implement GenAI, statistical models and machine learning algorithms to analyze diverse sources of data, ensuring they meet business requirements and are delivered on time. Use state-of-the-art methods to interpret and analyze data from multiple angles, identify patterns, trends, and insights. Present information using data visualization techniques to help stakeholders understand the significance of data insights. Build predictive models and machine-learning algorithms to forecast future trends and outcomes. Design and implement APIs for exposing data and models, ensuring they adhere to best practices in software engineering. Collaborate with developers, data scientists, and business teams to implement GenAI solutions. Stay abreast of the latest AI research and technologies, evaluating and adopting them to maintain our competitive edge. Communicate complex AI concepts to non-technical stakeholders, facilitating informed decision-making. Applies Software knowledge and experience to design, develop, create, modify, and validate software, applications, and/or specialized utility programs. Participates in the design, coding for large features, unit testing, significant debugging fixes, and integration efforts to ensure projects are completed to specifications and schedules. Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 2+ years of Software Engineering, Systems Engineering, or related work experience. Minimum of 2 years of experience in AI/ML technologies and 1 year of GenAI experience. Minimum of 2 years of strong experience in Application development using Python Proven track record of developing AI solutions and deploying to production environment. Deep understanding of AI/ML algorithms, data structures, and software engineering principles. Expertise with at least one cloud computing platforms (e.g., AWS, Azure, Google Cloud). Proficiency in Python, SQL and NoSQL databases. Familiarity with LLMs (like Open AI models, Llama), AI agent frameworks (like LangChain, LangGraph, CrewAI, Microsoft AutoGen), machine learning frameworks (like Keras, PyTorch, TensorFlow) and libraries (like scikit-learn). Excellent communication skills, with the ability to articulate technical concepts to a variety of audiences. Ability to thrive in a fast-paced and dynamic environment. Advanced degree (MS) in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or related quantitative field. Cloud Certified - Azure/AWS/GCP Strong debugging and analysis skills, for root causing complex issues. A minimum of 4 years of experience in data science, data analytics, or related field. Experience in designing and implementing solutions using LLMs, RAG, Vector databases, Sematic Search, Model fine-tuning. Strong knowledge of statistics and experience using statistical packages for analyzing datasets. Understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, CNN, Vision Transformers and LLMs etc. Experience in designing and implementing APIs for data engineering and models training and deployment pipelines. Experience working within large global matrix organizations.