Technical Project Manager

Natural Language Processing (NLP), Voice App Development, Data Structures & Algorithms, Web Development, Machine Learning, Deep Learning, Natural Language Processing, Data Science, Tableau, SAS Programming, SQL for Data Analytics, Power BI, Clinical Trial Analysis & Reporting, Git & GitHub

Project Planning and Management : Develop and execute comprehensive project plans, including scope, timelines, resources, and budget allocation. Define project milestones and deliverables, ensuring adherence to project management best practices throughout the project lifecycle.

Requirement Analysis : Collaborate with clients and stakeholders to gather and analyse business requirements. Translate these requirements into technical specifications and project deliverables. Identify any customization or integration needs and define the technical approach accordingly.

Solution Architecture : Create comprehensive AI/ML system designs, including architecture, data pipelines, algorithms, and model selection. Ensure that the solution aligns with business goals and is scalable and maintainable. Evaluate and select the most suitable AI/ML technologies, frameworks, and tools for each project. Stay up to date with emerging AI/ML trends and technologies.

Team Coordination : Lead and manage cross-functional project teams, including developers, consultants, and other stakeholders. Define roles and responsibilities, assign tasks, and provide guidance and support throughout the project lifecycle. Foster effective collaboration and communication among team members.

Risk and Issue Management : Identify and proactively mitigate project risks and issues. Develop contingency plans to address any potential obstacles that may arise during the project. Monitor project progress, track project metrics, and communicate project status to stakeholders, ensuring transparency and timely reporting.

Quality Assurance : Establish and enforce quality standards and best practices throughout the project. Conduct regular quality reviews and ensure adherence to coding standards, testing protocols, and documentation requirements. Perform thorough testing and coordinate user acceptance testing (UAT) activities.

Client Relationship Management : Build and maintain strong relationships with clients and stakeholders. Provide regular project updates, manage expectations, and address any concerns or issues that arise. Ensure a high level of client satisfaction by delivering projects that meet or exceed their expectations.

Continuous Improvement : AI/ML technologies are rapidly evolving. Stay current with the latest research, frameworks, algorithms, and best practices in AI/ML. Subscribe to relevant journals, blogs, and attend conferences and workshops. Invest in ongoing education and training for your AI/ML professionals. Provide opportunities for them to acquire new skills and certifications, attend training programs, and participate in online courses.

• Bachelor s degree in computer science, Information Technology, or a related field (master s degree preferred).

• Practical experience in at least one of Java, Python, or JavaScript.

• 8+ years of hardware engineering, software engineering, systems engineering and/or technical project management experience.

• Effective communication skills including uplevelling communication for various leadership levels.

• Experience moving technical or engineering programs and products from inception to delivery, articulating the impact using metrics.

• Collaborate with the team in solutioning, design, and code reviews.

• Analytical and problem-solving experience with large-scale systems.

• Experience establishing work relationships across multi-disciplinary teams working remotely.

• Interpersonal skills, including relationship building and collaboration within a diverse, cross-functional team to develop solutions.

• Organizational and coordination skills along with multitasking experience to get things done in an ambiguous and fast paced environment.

• Analytical mindset with the ability to identify and mitigate risks, solve problems, and make data-driven decisions.

• Strong organizational skills and attention to detail, with the ability to manage multiple projects simultaneously.

• Acquire, clean, and preprocess data from various sources to prepare it for analysis and modelling.

• Perform exploratory data analysis (EDA) to identify trends, patterns, and anomalies in the data.

• Design and implement data pipelines for efficient data processing and model training.

• Develop and maintain documentation for data processes, datasets, and models.

• Collaborate with data scientists to design and evaluate machine learning models.

• Monitor and assess the performance of machine learning models and make recommendations for improvements.

• Stay up to date with industry trends and best practices in AI/ML and data analysis.