Prakash Hullathi

Results-driven Data Analytics Leader with 16 years of experience driving data-driven decision-making, advanced analytics, and AI-driven transformation across diverse industries. In search of a senior leadership role to champion data-driven innovation, build high-performing analytics teams, and influence C-suite decision-making for enterprise-wide impact.

Extensive experience in the field of data analytics, with a strong emphasis on creating data-driven solutions and insights that enhance business decision-making processes across various sectors. Currently serving as a Principal Data Scientist, leading innovative projects that leverage Comprehensive skill set encompassing with a proven track record of applying these techniques to deliver high-impact results in analytics. Artificial intelligence, prompt engineering, machine learning, deep learning, generative ai, natural language processing, forecasting and advanced statistical techniques, predictive modeling to solve complex business challenges and drive operational efficiency. Adept at strategic planning, enterprise data architecture, and business intelligence, leveraging and big data analytics to unlock insights and optimize performance. Proven expertise in leading cross-functional teams, establishing data governance frameworks, and aligning analytics strategies with business objectives to drive revenue growth, operational efficiency, and competitive advantage. Crafting compelling data visualizations and dashboards that effectively communicate insights to stakeholders, enhancing their ability to make informed decisions based on data. In-depth knowledge of data integration techniques and the ability to design and implement robust data architectures that support real-time analytics and reporting. Computer Vision CNN,RCNN ,Tensorflow,Caffe Good in developing AI, ML and Gen AI RAG apps with streamlit and bentoml

• Enabling data-driven decision-making by analyzing business processes, customer experience trends, user journeys, and data insights to drive strategic business outcomes.
• Providing technical and strategic leadership in designing and implementing scalable, high-impact data science solutions that enhance operational efficiency and business growth.
• Collaborating with cross-functional teams to align data strategies with organizational goals, define key performance indicators (KPIs), and establish robust reporting frameworks.
• Integrating and harmonizing data from multiple sources into Power BI, ensuring data integrity, consistency, and accuracy for comprehensive analysis.
• Transforming raw data into actionable insights by leveraging DAX, Power BI Editor, and data modeling techniques, creating calculated measures, custom columns.
• Designing intuitive and impactful visualizations, deploying interactive dashboards via Power BI Service, managing access permissions, and utilizing One Lake Data Hub to ensure secure and efficient data distribution.
• Harnessing machine learning and AI capabilities, applying supervised, unsupervised, reinforcement, and deep learning algorithms to solve complex business problems and drive innovation.
• Developing and deploying AI-powered applications and predictive models to enhance forecasting accuracy and decision-making agility.
• Leading and mentoring data science teams, fostering a culture of analytical excellence, innovation, and best practices in machine learning and advanced analytics.
• Driving revenue growth through data-driven marketing strategies, including cross-sell and up-sell campaigns for personal finance and credit card retail products.
• Extracting actionable merchant insights from transaction data to develop targeted promotions and offers that optimize revenue streams.
• Building sophisticated recommendation engines using collaborative filtering and content-based filtering, enhancing personalization and customer engagement.
• Developing Next Best Offer (NBO) strategies with clear, data-backed recommendations to support strategic business decision-making.
• Leveraging NLP techniques to derive structured insights from Visa/Mastercard transaction merchant names, improving data classification and analytics.
• Constructing and implementing advanced statistical models, including correlation analysis, regression models, ARIMA, moving averages, exponential smoothing, and LSTM forecasting, to drive predictive insights and trend analysis.
• Developed Credit Risk Models in banking domain.
• Created machine-learning, AI and LLM Gen AI apps.