Job Summary:
We are seeking an experienced Lead Data Scientist to drive data-driven decision-making across the organization. In this role, you will translate business needs into analytics and reporting requirements, leading the development and operationalization of data science models to solve complex business problems. You will guide and mentor a team of data scientists, foster innovation, and ensure that analytical insights are embedded into business processes. Your expertise in advanced analytics, machine learning, and cloud computing will be critical in advancing our data science capabilities and delivering measurable business value.
Key Responsibilities:
- Business Translation & Requirement Gathering: Work closely with business stakeholders to translate business needs into analytics and reporting requirements, supporting data-driven decisions across the organization.
- Innovation & Technology Adoption: Stay updated on the latest data science techniques and technologies, exploring and implementing innovative solutions to enhance data analysis, modeling capabilities, and business outcomes.
- Communication & Advocacy: Communicate complex data insights clearly and effectively to both technical and non-technical stakeholders. Advocate for the importance of data-driven decision-making across the organization.
- Team Leadership & Development: Manage and guide use case design and build teams, providing day-to-day feedback and support. Ensure data science models and algorithms are developed, operationalized, and maintained to solve complex business problems.
- Model Deployment & Maintenance: Oversee the deployment and ongoing maintenance of data science models, ensuring they remain effective and continue to deliver value post-launch.
- Strategic Planning & Execution: Contribute to the long-term planning of the Data Science team, including talent acquisition, technology platform input, and interaction with other organizational units.
- Culture & Continuous Improvement: Foster a culture of innovation and continuous improvement, leading the adoption of new data science technologies and methodologies to enhance the organization’s analytics capabilities.
- Stakeholder Collaboration: Engage with a wide range of business and technical stakeholders to proactively identify opportunities for new technologies and data science applications, communicating how they can deliver measurable business value.
- Analytics Solution Portfolio Ownership: Own and manage the analytics solution portfolio, ensuring models are continuously improved and maintained over time.
Required Qualifications:
- Education: Master’s degree or PhD in Computer Science, Statistics, Applied Mathematics, or a related field.
- Experience: At least 5-7 years of experience in data science or a similar role, with a strong track record of delivering data-driven insights and solutions.
- Technical Expertise:
- Proficiency in at least one analytical programming language relevant to data science (Python preferred, R acceptable).
- Expertise in machine learning libraries and frameworks such as TensorFlow, PyTorch, and scikit-learn.
- Familiarity with data processing and visualization tools such as SQL, Tableau, and Power BI.
- Strong understanding of advanced analytical techniques, including supervised and unsupervised machine learning, descriptive statistics, optimization, pattern recognition, and cluster analysis.
- Experience with cloud computing environments like AWS, Azure, or GCP, and Data/ML platforms such as Databricks and Spark.
- Comprehensive knowledge of the machine learning lifecycle, including feature engineering, training, validation, scaling, deployment, monitoring, and feedback loops.
- Additional Skills:
- Experience with programming best practices, CI/CD pipelines, and building reusable, scalable data solutions.
- Strong leadership and communication skills, with the ability to work effectively across technical and non-technical teams.
