Role Summary
As a Data Science Lead at Worley, you will collaborate with an established team to deliver high-impact data science and AI/ML projects for clients, while continuing to expand your own technical expertise. The role focuses particularly on working with unstructured data and involves designing scalable AI/ML solutions, staying on the leading edge of technology, and driving innovation across both internal and external stakeholders.
Key Responsibilities
- Platform & Tool Development:
- Conceptualize, build, and manage AI/ML platforms with a focus on unstructured data.
- Evaluate and select the best AI/ML tools and frameworks in the industry.
- Leverage existing frameworks, standards, and patterns to create scalable architectural foundations.
- Solution Delivery & Ownership:
- Lead the development of cognitive solutions for both internal stakeholders and external customers.
- Conduct research in areas like Explainable AI, image segmentation, 3D object detection, and statistical methods.
- Ensure delivery of scalable, enterprise-grade applications and services.
- Strategic Insight & Innovation:
- Analyse global market trends (economic, social, cultural, technological) to identify AI/ML opportunities.
- Shape value propositions and recommendations using a global perspective.
- Evaluate algorithms, models, and emerging technologies to optimize organizational investment.
- Collaboration & Leadership:
- Guide and support data scientists and engineers in project execution involving large and complex datasets.
- Establish and oversee AI/ML lifecycle processes and best practices.
- Ensure collaboration across multi-disciplinary teams.
Technical Skills & Experience
- AI/ML Expertise:
- Deep understanding of the full AI/ML project life cycle.
- Expert in deep learning and reinforcement learning.
- Experience with MLOps practices for effective model lifecycle management.
- Proficient in machine learning algorithms: k-NN, GBM, Naive Bayes, SVM, Neural Networks, Decision Forests.
- Tools & Frameworks:
- Hands-on experience with tools such as:
- Jupyter Hub, Zeppelin Notebook, Azure ML Studio
- TensorFlow, TensorFlow-Keras, PyTorch, SciKit-Learn, Spark MLlib
- Strong knowledge of CNN, R-CNN, LSTM, Encoder/Transformer architectures.
- Experience with deep learning models like Inception-ResNet and ResNeXt-50.
- Proven use of RNNs for text, speech, and generative models.
- Data Engineering & Storage:
- Familiarity with NoSQL databases (GraphX, Neo4J), document, columnar, and in-memory data models.
- Experience with ETL tools and platforms such as Talend, SAP BI Platform, SSIS, and MapReduce.
- Visualization & Reporting:
- Skilled in building KPI dashboards and storytelling visuals using tools like Tableau or Zoomdata.
Preferred Qualifications
- Advanced degree in Data Science, Computer Science, AI/ML, or related fields.
- Demonstrated leadership in managing AI/ML projects and teams.
- Prior experience in consulting or energy/resources industries is a plus.
