About the Role We are seeking a Technical/Product Marketing Manager with deep knowledge of RegTech / FinTech products and strong technical acumen. This role bridges product, marketing, and sales by translating complex product capabilities into clear, compelling value propositions for financial institutions, compliance officers, and technical buyers. Key Responsibilities Product Positioning & Messaging Develop and refine product messaging that resonates with decision-makers in banks, MSBs, EMIs, and PSPs. Create technical marketing content (whitepapers, solution briefs, product videos, explainer decks, ROI calculators). Translate compliance and technical features into customer-centric benefits. Sales Enablement Collaborate with Sales to develop battle cards, demo scripts, and objection-handling tools. Support sales pitches with technical insights and product use cases. Train internal teams on product capabilities and market positioning. Go-to-Market Strategy Partner with Product and Marketing to define launch plans for new features/modules. Create segmented campaigns targeting compliance teams, CTOs, risk officers, and operations heads. Conduct competitor and industry analysis to inform positioning. Technical Content & Thought Leadership Author and manage technical blogs, compliance explainers, solution guides, and product comparisons. Represent the company at industry events, webinars, and customer meetings. Customer and Market Insights Collaborate with Customer Success and Product to capture user feedback and turn it into marketing insights. Stay updated on changing regulations (e.g., FATF, FINTRAC, MAS, GDPR) and how they impact product marketing. Requirements 5-8 years in B2B marketing, with at least 3 in a FinTech/RegTech or SaaS environment. Strong understanding of AML, KYC, fraud monitoring, or compliance software products. Ability to understand and explain technical product architecture, API/SDK integrations, and modular offerings. Exceptional communication and storytelling skills. Experience creating high-impact marketing assets for technical and compliance audiences. Experience with tools like HubSpot, Salesforce, Figma, and basic understanding of analytics tools. Preferred Prior experience marketing to compliance or risk management personas. Understanding of cloud-native architectures (e.g., AWS, microservices, serverless). Knowledge of financial regulations in key markets (Canada, Singapore, India, UK, EU).

We are looking for a data scientist who will help us discover the information hidden in vast amounts of data, and help us make smarter decisions to deliver AI/ML based Enterprise Software Products. Develop solutions related to machine learning, natural language processing and deep learning & Generative AI to address business needs. Your primary focus will be in applying Language/Vision techniques, developing llm based applications and building high quality prediction systems. Analyze Data: Collaborate with cross-functional teams to understand data requirements and identify relevant data sources. Analyze and preprocess data to extract valuable insights and ensure data quality. Evaluation and Optimization: Evaluate model performance using appropriate metrics and iterate on solutions to enhance performance and accuracy. Continuously optimize algorithms and models to adapt to evolving business requirements. Documentation and Reporting: Document methodologies, findings, and outcomes in clear and concise reports. Communicate results effectively to technical and non-technical stakeholders. Work experience background required Experience building software from the ground up in a corporate or startup environment. Essential skillsets required: 5-15 years experience in software development Educational Background: Strong computer science and Math/Statistics Experience with Open Source LLM and Langchain Framework and designing efficient prompt for LLMs. Proven ability with NLP and text-based extraction techniques. Experience in Generative AI technologies, such as diffusion and/or language models. Excellent understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests, etc. Familiarity with cloud computing platforms such as GCP or AWS. Experience to deploy and monitor model in cloud environment. Experience with common data science toolkits, such as NumPy, Pandas etc Proficiency in using query languages such as SQL Good applied statistics skills, such as distributions, statistical testing, regression, etc. Experience working with large data sets along with data modeling, language development, and database technologies Knowledge in Machine Learning and Deep Learning frameworks (e.g., TensorFlow, Keras, Scikit-Learn, CNTK, or PyTorch), NLP, Recommender systems, personalization, Segmentation, microservices architecture and API development. Ability to adapt to a fast-paced, dynamic work environment and learn new technologies quickly. Excellent verbal and written communication skills