About the Role
The Senior Data Scientist is a key role within the Data Science team that involves leading complex data analysis and model development projects, leveraging a deep understanding of data science and machine learning workflows. This role requires the ability to navigate fast-paced environments with agility and poise, as well as build strong partnerships with engineering, product, business, finance, and analytics teams. As a Senior Data Scientist, you will take on a leadership position, guiding junior team members and ensuring the successful implementation of advanced analytics solutions.
Key Responsibilities
- Help execute data science strategies and roadmaps to address business challenges and opportunities through analytics and AI/ML models.
- Hands on design, development, and deployment of predictive models, machine learning algorithms, and AI solutions.
- Collaborate with team members and business stakeholders to understand objectives and requirements and develop analytic models that provide actionable insights.
- Ensure the validity, reliability, and robustness of models by implementing best practices in model validation, testing, and calibration.
- Monitor performance and outcomes of models and refine them for optimized performance.
- Communicate complex analytic solutions and insights in a clear and structured manner to business stakeholders.
- Foster a culture of continuous improvement within our data science practices, staying abreast of industry trends and advancements.
- Demonstrate an eagerness to learn, including aspects related to bringing data science models into operational use.
Qualifications
- Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, or related field. PhD in the above fields preferred.
- Minimum of 5 years of experience in a data science role, showcasing solid abilities in SQL and Python.
- Excellent data analysis, profiling and statistics skills coupled with proficiency in SQL tools and technologies such as Oracle, SQL Server, MySQL, Pandas, NumPy, ggplot, Shiny, SciPy, Sci-Kit Learn, and Matplotlib.
- Proficiency in utilizing a range of Machine/Deep Learning algorithms and frameworks, including TensorFlow, PyTorch, scikit-learn, Spark ML, Torch, Huggingface, Keras, Caffe, and CNTK.
- Solid understanding of cloud computing environments and experience with deploying models in cloud environments such as AWS, Azure, or GCP.
- Experience in or understanding of model development, with a willingness to explore model deployment strategies.
- High analytical aptitude for navigating complex datasets to extract actionable insights.
- Excellent problem-solving skills and a detail-oriented mindset.
- Strong communication abilities, capable of conveying technical concepts to diverse audiences.
- Proactive in learning and adapting to new methodologies and challenges.
- Ability to work effectively in a team and manage simultaneous projects in a dynamic environment.
Nice to Have
- Prior experience in Fintech
- Software engineering experience