Data Scientist

As a Data Scientist at our company, you will be responsible for designing, developing, and deploying intelligent agents using LangChain and LangGraph frameworks to optimize conversational AI workflows. You will also build, deploy, and optimize data models focused on generative AI and large language models. Your role will involve creating and refining methods to measure AI model performance and impact, as well as collaborating with product and engineering teams to integrate AI solutions such as Gemini, OpenAI, and Azure AI. It is essential to stay current on advances in data science, machine learning, and generative AI while mentoring junior data scientists and engineers. Clear communication with stakeholders to present insights and recommendations will be a key aspect of your responsibilities. Additionally, applying statistical, econometric, and machine learning methods to generate actionable insights and support decision-making, identifying and leveraging key data sources to enhance analytics, developing scalable data structures and analytic products, and leading end-to-end analytics projects will be part of your daily tasks. Providing insights to encourage data-driven decision-making throughout the organization, mentoring teams on data science best practices, contributing thought leadership through blogs or articles, delivering training on analytics tools and data science techniques, and exploring and applying new data science tools and methodologies to maintain innovation are also important aspects of the role. Qualifications required for this position include a Bachelor's degree, with an advanced degree (Masters or Ph.D.) in Data Science, Statistics, Econometrics, Computer Science, or related field strongly preferred. You should have at least 5 years of professional experience as a Data Scientist, particularly within areas such as Sales, Finance, Product, Strategy, or Marketing in the software or technology industry. Strong programming skills in Python and R, including familiarity with advanced analytics libraries and frameworks, expertise in statistical methods, econometrics, machine learning algorithms, artificial intelligence, and predictive analytics, as well as experience in developing scalable analytic data strategies and robust analytic products are necessary qualifications. Proficiency with visualization tools such as Tableau, experience in business analytics platforms like Alteryx, familiarity with data pipelines, ETL processes, cloud databases, data warehouses (e.g., Snowflake), and data lakes, experience deploying analytics solutions in cloud environments (GCP, AWS & Azure), strong communication skills, excellent problem-solving abilities, and interpersonal skills are also key requirements for this role.,