Senior Data Scientist II

<p></p><p></p><p></p><p>Senior Data Scientist II</p><p></p><p></p><p>Are you eager to create the best possible data science solutions that help solve customer (e.g. researchers, authors, editors) problems? </p><p></p><p></p><p>Do you want to develop decision support tools to help making faster and better decisions?</p><p></p><p>About the Role</p><p>As a Senior Data Scientist II, you will play a pivotal role in advancing our data science initiatives by leading the strategic development and implementation of NLP solutions. This position involves overseeing the entire lifecycle of complex data science projects, contributing to the refinement of models, and providing mentorship to junior data scientists. Collaboration with cross-functional teams will be crucial to innovate and scale our data science capabilities.</p><p></p><p>Responsibilities</p><ul><li>Strategic Data Insights and Model Development: Lead the development of advanced models with a focus on classification, deep learning, and innovative techniques. Spearhead data collection and analysis, define quality metrics, and present high-level insights to stakeholders. Provide guidance and mentorship to junior team members.</li><li>Advanced Production Solutions: Design sophisticated, production-ready Python packages for data science pipelines, ensuring seamless deployment and scalability. Collaborate extensively with technology teams to enhance production solutions.</li><li>End-to-End Integration and Quality Assurance Leadership: Take a leadership role in integrating data science components, conducting rigorous quality assessments, and leveraging expertise in large language models. Establish resilience against model drift and develop comprehensive maintenance strategies, including automated model re-training protocols.</li><li>Performance Evaluation and Strategic Development: Develop comprehensive reporting mechanisms for pipeline performance and lead the implementation of automatic re-training strategies, ensuring continuous optimization.</li></ul><p></p><p>Requirements</p><ul><li>Education and Experience: Minimum of 4 years of relevant industry experience and a Master's degree or higher in computer science, data science, artificial intelligence, mathematics, statistics, or related quantitative fields. A Ph.D. is highly preferred. Considerable experience leading complex data science projects is essential.</li><li>Advanced Programming Proficiency: Proven expertise in Python, delivering high-quality, production-ready code following best practices. Provide mentorship in advanced programming to junior team members.</li><li>Advanced Natural Language Processing Expertise: Proven experience in applying NLP to solve complex problems, particularly in large language models and sophisticated NLP tasks.</li><li>Advanced Machine Learning Expertise: Extensive hands-on experience in advanced classification, regression, clustering, and deep learning techniques. Mastery in neural networks, large language models, and cutting-edge ML algorithms. Expertise in Scikit-learn, PyTorch, and/or Tensorflow at an advanced level.</li><li>Deep Knowledge of Large Language Models: Mastery in utilizing and integrating large language models for sophisticated natural language processing tasks, guiding the team effectively.</li><li>Expert Data Manipulation Skills: Mastery in data processing, cleaning, and analysis, with advanced expertise in tools like Pandas, NumPy, Matplotlib, and SciPy.</li><li>Advanced Communication Skills: Exceptional communication and presentation skills, conveying complex data science concepts to both technical and non-technical stakeholders.</li><li>Strategic Analytical Thinking: Demonstrated ability to strategically solve complex problems and translate intricate requirements into effective solutions.</li><li>Expert Technical Competence: Advanced proficiency in Git, DevOps, CI/CD, and extensive experience in cloud computing platforms like AWS and Azure.</li><li>Continuous Learning and Mentorship: Demonstrate commitment to continuous learning and a keen interest in mentoring junior team members, driving innovation, and staying updated in MLOps and data science productionization.</li></ul><p></p><p>Nice to Have</p><ul><li>Extensive experience in optimizing productionization using parallelization, multi-threading, and automated model re-training.</li><li>Proficiency in MLOps frameworks (e.g., SageMaker, Kubeflow, MLFlow) and big data processing frameworks (e.g., Spark, Hadoop, Databricks).</li><li>Advanced software engineering skills, including proficiency in additional programming languages like Java and SQL, along with comprehensive knowledge of relational databases, semi-structured and unstructured document formats (e.g., JSON and XML), REST interfaces, micro-services, and UML.</li></ul><p></p><p>Work in a way that works for you</p><p></p><p>We promote a healthy work/life balance across the organisation. With an average length of service of 9 years, we are confident t