Palladium is a global leader in the design, development and delivery of Positive Impact – the intentional creation of enduring social and economic value. We work with governments, businesses, and investors to solve the world's most pressing challenges. With a team of more than 3,000 employees operating in 90 plus countries and a global network of over 35,000 experts, we help improve economies, societies and, most importantly, people's lives.
Purpose Of Position
Palladium is seeking skilled Data Scientist to work with the data analytics, and health informatics team in Data.FI responsible for the design and development of various technology products that support health and social services. The incumbent will work in collaboration with the health informatics, and data analytics and use team to design and execute data science projects. He/she will primarily support HIV/AIDS and TB focused data and analytics projects. Envisioned activities relate to population and patient health using supervised and unsupervised machine learning and other data science tools. Applications leverage deidentified patient data, aggregate health reporting data, survey data, and geospatial data, among others. Experience with health applications, particularly using sparse and/or poor-quality data and data related to developing countries, is preferred. Projects will result in outputs ranging from reports and analyses to deployed models generating information for decision makers in real time.
The Data Scientist will report to the Senior Manager Data Analytics and Use, and work closely with Business Analytics, Health Informatics and Public Health Surveillance Teams. This is full-time position with a contract for 1 year, renewable subject to availability of funding.
Location: Abuja, Nigeria. The position will entail approximately 10-15% local travel.
Primary Duties And Responsibilities
- Lead data cleaning, including identification of data quality issues (such as missing or mislabelled data or extreme values) and identifying and executing cleaning steps
- Lead in the design, develop, and deploy scalable machine learning models and architectures.
- Collaborate with cross-functional teams to integrate ML solutions into existing systems.
- Develop and maintain large-scale datasets for model training and testing.
- Collaborate with data analytic team in Implementing data preprocessing, feature engineering, and data visualization techniques of ML products.
- Train, test, and deploy models using various ML frameworks (e.g., TensorFlow, PyTorch).
- Ensure model reliability, scalability, and maintainability.
- Monitor model performance and retrain as necessary.
- Work closely with cross functional team (data analysts, devOps engineers, and business analyst) to identify opportunities for ML applications.
- Lead the communication of complex technical concepts to non-technical stakeholders.
- Conduct periodic code reviews and ensure high-quality code on ML/AI activities.
Required Qualifications
- A degree in Computer Science, , Mathematics, Statistics, or related field
- An advanced degree in Computer Science, Data Science, Machine Learning or related field will be an added advantage.
- Minimum 5 years of hands-on experience in machine learning/artificial intelligence, with a strong track record of delivering scalable and reliable ML/AI solutions.
- Proficiency in Python, R, Java, C++
- Expertise in ML frameworks: TensorFlow, PyTorch, Keras
- Familiarity with data preprocessing, feature engineering, and data visualization
- Good understanding of machine learning algorithms and techniques, including supervised and unsupervised learning, regression, classification, and clustering.
- Good understanding of statistical concepts and methods such as hypothesis testing, regression analysis, probability distributions, and Bayesian inference.
- Knowledge of database management systems and query languages (e.g., SQL)
- Experience with cloud platforms (e.g., AWS, GCP, Azure)
- Familiarity with containerization (e.g., Docker)
- Excellent written and verbal communication skills.
- Ability to work in a dynamic and agile environment with changing requirements and priorities.
- Knowledge and experience applying the Principles for Digital Development.
- Demonstrated ability to work effectively with team members and clients of different cultures, gender, and hierarchical levels.
Professional Expertise/Competencies Preferred
- Detail-oriented and deadline-driven with strong organizational skills
- Highly self-motivated and able to work independently as well as in team settings
- Strong communication and interpersonal skills
- Expertise in visualizing and manipulating big datasets
- Ability to select hardware to run an ML model with the required latency
- Demonstrated ability to work effectively as a member of a fast-moving and multicultural team while maintaining a client-centered focus
- Familiarity with a wide range of machine learning algorithms including supervised learning (e.g., linear regression, decision trees, random forests, SVMs), unsupervised learning (e.g., clustering, dimensionality reduction), and deep learning (e.g., neural networks, CNNs, RNNs)
- Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
- Experience with large language model(LLM), Generative AI, deep learning, and prompt engineering.
Method of Application
Signup to view application details.
Signup Now
