Data Scientist

7 months ago

Stellenbosch, South Africa Unifi Recruitment Full time

**Job Advert Summary**:
Unifi is a fast-growing finance and technology company operating in Zambia, South Africa, Uganda and Kenya.
Unifi delivers personal lending products through online, mobile phone and branch channels. The company is
well supported by strong shareholders and a board of directors with vast experience in entrepreneurship and
lending.

Unifi is recruiting a new **Data Scientist** with experience in Python, SAS, Google Looker and BigQuery to join our
visualizations to help our organization make data-driven decisions. They will also work closely with
stakeholders to understand their requirements and develop solutions that meet their needs. Be a proficient
specialist who applies mathematical, problem-solving, and coding skills to manage big data, extracting valuable
insights.

environment and have a passion for African business. A healthy spirit of adventure and sense of humour would
be helpful.

As a **Data Scientist**, you will play a critical role in collecting, analyzing, and interpreting data to
drive informed decision-making within our organization. You will be responsible for extracting insights,
identifying trends, and presenting findings to key stakeholders. Your work will contribute to improving
operational efficiency, optimizing business processes, and enhancing overall performance.

**Minimum Requirements**:

- Bachelor's or master's degree in a relevant field (e.g., Mathematics, Statistics, Computer Science, Data
Analytics/Science);
- Proven experience as a Data Scientist or similar role win min experience of 3+ years;
- Proficiency in data analysis tools GCP (Google Cloud Platform), Google Big Query, SAS, SQL, Python, R
and data visualization tools Google Looker;
- Strong analytical and problem-solving skills with a keen attention to detail;
- Ability to handle and analyse large datasets efficiently;
- Experience with statistical analysis techniques and data modelling;
- Excellent communication and presentation skills;
- Proficiency in Microsoft Excel and other data manipulation tools;
- Familiarity with data governance principles and best practices;
- Knowledge of data privacy regulations and compliance standards is a plus.

**Duties and Responsibilities**:
**1. Data Collection and Cleaning**:

- Collect, extract, and compile data from various sources, ensuring data accuracy and
completeness;
- Clean and transform raw data into structured datasets for analysis;
- Identify and resolve data quality issues, inconsistencies, and anomalies;
- Utilizing the technologies of SQL, SAS, Python and Big Query, while staying up-to-date with
latest trends and developments in data analytics.

**2. Data Analysis and Interpretation**:

- Perform exploratory data analysis to identify trends, patterns, and relationships within the
data;
- Analyse large and complex datasets to derive actionable insights and recommendations;
- Collaborate with stakeholders to understand business requirements and translate them into
analytical approaches.

**3. Reporting and Visualization**:

- Create visualizations, dashboards, and reports to effectively communicate data insights to
stakeholders with help of Google Looker;
- Develop and maintain standardized reporting templates and data visualization tools;
- Present findings in a clear and concise manner, tailoring the information to the audience's
needs.

**4. Data-driven Decision Making**:

- Collaborate with cross-functional teams to support data-driven decision-making processes;
- Provide analytical support for business initiatives, including market analysis, customer
segmentation, and performance tracking;
- Identify opportunities for process improvement, operational efficiencies, and revenue
optimization based on data analysis.

**5. Data Governance and Security**:

- Ensure compliance with data governance policies, data protection regulations, and security
protocols;
- Adhere to data privacy and confidentiality standards when handling sensitive information;
- Contribute to the development and maintenance of data dictionaries and data
documentation.

**6. Continuous Learning and Development**:

- Stay updated with industry trends, best practices, and emerging technologies in data analysis;
- Expand knowledge of statistical analysis techniques, data modelling, and data visualization
tools;
- Participate in training programs, workshops, and professional development opportunities.

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