We are looking for a talented Data Scientist to lead projects in the Data Science/AI and Data Architecture/Engineering areas. Provide SME support on Digital Transformation and Smart City/Smart District consulting projects, along with presales and product development efforts. Also provide data architecture and engineering support on data management projects related to data quality and master data management.
- Understand and interpret business challenges around Data Science and AI solutions.
- Partner effectively with cross-functional partners to translate business needs into analytical requirements.
- Help our clients make better business decisions by transforming an ocean of data into streams of insight.
- Communicate the results of analyses in a clear and effective manner with leadership teams and stakeholders to influence the overall strategy of the implementation.
- Be technically adept with the latest trends, platforms, and challenges around ML/AI.
- Ensure that the risks associated with projects are raised proactively to ensure all projects stay on track.
- Build complex predictive models using ML and DL techniques with production quality code and jointly own complex data science workflows with the Data Engineering team.
- Have a business mindset towards problem solving in combination with tech passion.
- Work closely around structuring solutions and proposals for opportunities in the pipeline.
- Coordinate with different functional teams to implement models and monitor outcomes.
- Support the presales and product development teams with relevant content and artifacts.
- 7+ years of experience in implementing analytic solutions.
- 5+ years of experience in a business-focused Data Scientist role.
- Firm understanding of data modelling and metadata schema development.
- Familiarity with ETL / BI concepts and processes, and third-party data inventory tools (e.g., CKAN).
- Passion for evangelizing the vision of data managed as an asset (Managing data as an asset means improving links between siloed databases and data stores; making information easier to find on-line, making it easier for analysts and policy makers to quickly access and transform data into new formats and knowledge.).
- Ability to design iterative and efficient processes for managing and opening data assets across an enterprise.
- Ability to lead working meetings with client teams and drive clients on tasks.
- Proven experience working in the Telecom industry (both Network and Business).
- Ability to build architecture and develop workflow for large-scale batch and streaming machine-learning systems and ability to deploy using docker/Kubernetes and/or create restful API interfaces
- Hands-on exposure to the following areas:
- Machine Learning (algorithms and math behind them, feature engineering, etc.).
- Programming (Python, R, Matlab, etc.).
- Operations Research (decision support systems, optimization techniques, etc.).
- Data Modeling (SQL / noSQL skills, ETL creation, database design, etc.).
- Deep learning techniques and working with open-source libraries like opencv and NLP libraries like spacy, huggingface etc.
Last updated on Oct 13, 2023