Lead Data Scientist

6 months ago

Johannesburg, South Africa Absa Bank Limited Full time

Empowering Africa’s tomorrow, together one story at a time.
- With over 100 years of rich history and strongly positioned as a local bank with regional and international expertise, a career with our family offers the opportunity to be part of this exciting growth journey, to reset our future and shape our destiny as a proudly African group.Job Summary

Work collaboratively across the business area to assess the key business challenges that can be solved by data & translate these requirements into data driven solutions for the area. Work on high value & high complexity data science problems & leverage deep data science expertise in advanced statistics, data wrangling, data mining, data analysis, feature engineering &predictive modeling, storytelling, distributed computing & data visualisation, machine learning tools & data intuition to operationalize & continuously improve data solutions that deliver relevant, quality assured, accurate & commercially impactful data to the business.

**Job Description**:
Data Science
- Develop machine learning and AI solutions for integration with business processes and systems
- Develop a deep understanding of the business area and associated challenges
- Cascade business challenges & commercial understanding to the data science team working on data solutions
- Further translate the business challenges into key questions that can be solved with data solutions & coach other data scientists to do the same
- Lead design thinking processes & leverage own deep design thinking skills to determine & confirm hypotheses and priority questions / data challenges & related metrics to be solved for
- Translate vague questions into specific & more tangible data analysis
- Translate this business understanding into data requirements & define a data strategy to deliver against these requirements
- Proactively partner with the data engineering team to refine the data requirements and develop a technical roadmap to deliver raw data to Data Science teams for interpretation & analysis
- Design fit for purpose data interpretation & analysis approaches & create customized data models, algorithms, machine learning tools and recommendation engines to achieve the desired business outcomes
- Use advanced data science skills to mine & interpret data. These include but are not limited to: advanced statistics, data wrangling, data mining, data analysis, feature engineering & predictive modeling, distributed computing, machine learning tools & data intuition
- Leverage the above to analyse & interpret complex data sets & manage large data volumes
- Develop data quality assurance frameworks and tools to test model & analysis techniques (e.g. algorithms, models) & overall data quality
- Translate analysis (make inferences & reach conclusions) into commercially relevant business insights & leverage storytelling and data visualization techniques to maximize impact & deliver a user friendly product to business
- Consolidate data solutions into viable end products (in the language of business) that can be leveraged on an ongoing basis e.g. dashboards, reports etc.
- Workshop data analysis (trends, insights, forecasts) & findings with business & show tangible business impact to be derived from the data science process
- Regularly refine data analysis based on business inputs leading to the finalization of the data solution
- Provide tangible, practical & commercially viable recommendations to the business based on the outcomes of the analysis & influence business decision making (even if it at times means delivering difficult messages)
- Proactively partner the data engineering teams to assess the effectiveness and accuracy of new data sources & data gathering techniques
- Positively contribute to the data architecture direction by providing expertise on data science tools, techniques and the broader business data requirements
- Promote data literacy across the enterprise by sharing best practices and showing tangible business impact & recommendations as a direct result of the the data solutions provided
- Proactively stay ahead of the curve on data science trends & leading practice data science tools and techniques & transition the organisation to advanced methods for the continuous optimization of data

Risk & Governance
- Identify data risks and mitigate these (pre, during & post solution deployment / data delivery)
- Create business cases & solution specifications for various governance processes (if required)
- Create knowledge & document management processes and practices for data management aligned to Group Risk, Governance & Compliance & Broader Regulatory requirements
- Provide risk, governance, compliance & broader regulatory reporting as required
- Contribute to risk, governance, compliance & broader regulatory processes as a data science expert (if & when required)
- Deliver on time & on budget (always)

People
- Coach & mentor other data scientists
- Conduct peer reviews, testing, problem solving

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