Lead Data Scientist, Data & AI Engr

at  NCS

QUALIFICATIONS:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
• 7+ years of experience in data science, with a strong background in statistical modeling, machine learning, and advanced analytics.
• 3+ years in a leadership or management role, preferably in an IT or Systems Integration environment.
• Proven experience in building and deploying data science solutions in real-world applications.
• Expertise in programming languages such as Python and SQL.
• Experience with data processing frameworks such as Hadoop, Spark, or similar.
• Hands-on experience with machine learning frameworks and libraries (e.g., TensorFlow, Keras, Scikit-learn).
• Proficiency in using visualization tools (e.g., Tableau, Power BI, matplotlib) to communicate findings.
• Strong problem-solving skills and ability to work in fast-paced environments.
• Excellent communication and presentation skills, with the ability to translate complex data into actionable insights.
• Collaborative team player with a passion for mentoring and guiding junior talent.
• Singaporean only

ROLE SUMMARY:

The ideal candidate will be responsible for driving data-driven initiatives, managing a team of data scientists, and collaborating closely with cross-functional teams to deliver innovative data solutions for clients.

KEY RESPONSIBILITIES:

• Lead and mentor a team of data scientists, analysts, and machine learning engineers.
• Define and execute data science strategy aligned with business objectives and client needs.
• Identify and prioritize data science initiatives to drive business impact and innovation.
• Develop and implement predictive models, machine learning algorithms, and statistical analyses to solve complex business problems.
• Work with large datasets, and perform data wrangling, cleaning, and feature engineering to build accurate models.
• Apply deep learning techniques, natural language processing (NLP), computer vision, or other advanced techniques as required by project needs.
• Partner with internal teams (software developers, data engineers, business analysts) and external clients to understand requirements and deliver tailored data solutions.
• Present insights, analytics, and models to stakeholders and clients in a clear and actionable manner.
• Work with the sales and business development teams to identify opportunities for data science-led solutions for clients.
• Oversee the design and implementation of data pipelines, ETL processes, and cloud-based data solutions.
• Collaborate with IT and engineering teams to ensure integration of data science models into production systems.
• Stay updated on emerging technologies, tools, and trends in the field of data science and machine learning.
• Promote a culture of continuous learning, experimentation, and improvement within the team.
• Evaluate new tools, platforms, and techniques to enhance the team’s capabilities and effectiveness.