Lead Data Scientist

Summary

Join Thoughtworks as a Data Scientist and lead impactful data science projects from conception to deployment. You will collaborate with cross-functional teams, leveraging advanced statistical modeling, machine learning, and AI techniques to solve complex business challenges. Responsibilities include designing experiments, selecting optimal models, and communicating findings to both technical and non-technical stakeholders. You will champion ethical AI practices and contribute to a data-literate culture. Thoughtworks offers a supportive environment with opportunities for professional development and growth. This role requires strong technical skills in data science, experience with GCP Cloud, and proven leadership abilities. The ideal candidate is a resilient problem-solver, adept at stakeholder management, and passionate about mentoring others.

Requirements

• Have advanced English skills
• Have experience with GCP Cloud
• Have experience in leading the analysis and modeling of different datasets and overseeing an inception to deploying and productionizing the models
• Have experience with statistical modeling, hypothesis testing, machine learning, deep learning, optimization and other data science techniques to implement end-to-end data science projects
• Understand the specialized areas of AI and possess a speciality with at least one of them (i.e.: NLP/computer vision/Generative AI, etc)
• Have experience with R, Python or equivalent statistical/data analysis tools and can write production-ready code that is easy to evolve and test
• Gather and preprocess large volumes of structured and unstructured data from various sources, ensuring data quality and integrity
• Analyze datasets using statistical and visualization techniques to identify patterns, trends and relationships
• Develop and implement machine learning models, algorithms and predictive analytics to solve specific business problems or improve existing processes
• Evaluate model performance using appropriate metrics and validate models to ensure robustness and reliability
• Interpret and effectively communicate findings and insights to non-technical stakeholders through reports, presentations and visualizations
• Ensure compliance with data privacy regulations and ethical standards when handling sensitive information
• Understand the importance of stakeholder management and can easily liaise between clients and other key stakeholders throughout projects, ensuring buy-in and gaining trust along the way
• Be resilient in ambiguous situations and can adapt your role to approach challenges from multiple perspectives
• Not shy away from risks or conflicts, instead take them on and skillfully manage them
• Be eager to coach, mentor and motivate others and aspire to influence teammates to take positive action and accountability for their work
• Enjoy influencing others and always advocate for technical excellence while being open to change when needed
• Be a proven leader with a track record of encouraging teammates in their professional development and relationships
• Have a natural ability to cultivate strong partnerships; understand the importance of relationship building and how it can bring new opportunities to our business

Responsibilities

• Lead and manage data science projects from inception to completion, including goal-setting, scope definition and ensuring on-time delivery with cross team collaboration
• Collaborate with stakeholders to understand their strategic objectives and identify opportunities to leverage data and data quality for enabling AI and machine learning
• Be responsible for the overall AI system design, problem framing and governance, identifying and managing risks and issues
• Design, develop and implement data science strategies that drive measurable business results
• Design experiments for the team to rapidly test ideas and assumptions, and identify future courses of action
• Use quality metrics to select machine learning models that will be deployed in the production environment
• Communicate technical findings and insights to stakeholders in a clear, easy and concise way, keeping the stakeholders in mind
• Contribute to the growth of the data science community along with promoting a culture of data literacy within the organization
• Address ethical concerns and adhere to ethical guidelines using FATTER AI (fairness, accountability, transparency, trustworthiness, explainability, responsibility)
• Work with CD4ML practices and data versioning tools

Benefits

Learning & Development opportunities