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.
Responsibilities:
Strategic
- 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.
Operational
- 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.
People Management
- Coordinate with different functional teams to implement models and monitor outcomes.
- Support the presales and product development teams with relevant content and artifacts.
Requirements
- 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.
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Last updated on Oct 13, 2023