Data Scientist

Job Description

Role & responsibilities Key Responsibilities: Analyze large and complex data sets to identify patterns, trends, and actionable insights using AI techniques. Develop and implement AI models, including machine learning, deep learning, and natural language processing algorithms, to address client-specific challenges. Design, develop, test, and deploy scalable AI solutions in production environments (a plus) Collaborate with cross-functional teams, including consultants and industry experts, to understand client needs and deliver AI-driven solutions. Communicate findings and insights effectively to both technical and non-technical stakeholders. Continuously improve existing AI models and algorithms to enhance their accuracy and efficiency Stay up to date with the latest advancements in AI, machine learning, and deep learning, and apply them to client projects. Contribute to the development and maintenance of AI infrastructure and tools. Qualifications: Bachelors or masters degree in Statistics, Computer Science, Engineering, or a related field Corporate Finance knowledge/interest is a plus. Familiarity with Agile methodologies and experience working in Agile teams. A product improvement mindset, with a focus on iterating and enhancing AI solutions. Minimum of 3 years of work experience in data science or a related field with a focus on AI Strong knowledge of AI techniques (knowledge of Rag Implementation and Agents) including machine learning, deep learning, and natural language processing Proficiency in Python and related libraries (e.g., Pandas, NumPy, scikit-learn, streamlit) is mandatory. Proficiency in querying language like SQL Experience with AI and machine learning frameworks and libraries (e.g., TensorFlow, PyTorch) Strong problem-solving skills and attention to detail Good presentation and communication skills, with a knack for explaining complex analytical concepts to people from other fields. A proactive learning attitude and willingness to stay current with industry trends and technologies. Experience working in a collaborative team environment. Strong development skills, including software engineering best practices (e.g., version control, testing, code reviews) Experience with cloud platforms (e.g., AWS, Azure, Google Cloud)