Lead/Senior Data Scientist - WFH

Discover your 100% YOU with us!

Position: Lead/Senior Data Scientist
Work setup & shift: WFH | Dayshift

Why join us?

You'll have:

Competitive Rewards: Enjoy above-market compensation, healthcare coverage on day one, plus one or more dependents, paid time-off with cash conversion, group life insurance, and performance bonuses
A Collaborative Spirit: Contribute to a positive and engaging work environment by participating in company-sponsored events and activities.
Work-Life Harmony: Enjoy the balance between work and life that suits you with flexible work arrangements.
Career Growth: Take advantage of opportunities for continuous learning and career advancement.
Inclusive Teamwork: Be part of a team that celebrates diversity and fosters an inclusive culture.

Role Objectives
This role requires an ability to:

Guide and mentor a high-performing Data Science team, aligning with best practices and industry standards.
Oversee planning and execution of Data Science initiatives, ensuring feasibility and alignment with organisational goals.
Conduct R&D, exploring new tools and methods while documenting findings for future projects.
Lead improvements to data ingestion pipelines, optimising structure, reliability, and performance.
Champion automation to streamline manual processes and reduce inefficiencies, including quality assurance.
Ensure data quality and integrity by implementing monitoring frameworks for internal and external sources.
Develop and refine predictive models, collaborating with cross-functional teams to address commercial and technical needs.
Coordinate with Engineering, Product, and Commercial teams to implement scalable solutions.
Communicate insights and recommendations clearly to stakeholders and leadership.

What We’re Looking For
To be successful in the role you'll ideally have:

5+ Years Experience in data science roles.
Experience mentoring or leading Data Science teams.
Proficiency in Python or R, SQL, and relevant data analytics libraries.
Strong understanding of data ingestion, pipeline design, and automation frameworks.
Expertise in statistical modeling, machine learning techniques, and algorithm development.
Proven track record in implementing QA processes and maintaining data quality standards.
Hands-on experience with cloud platforms (e.g. AWS, Azure, GCP) and scalable data architectures.
Ability to document technical processes and communicate complex insights to both technical and non-technical audiences.
Strong problem solving skills.
Great communication with an ability to collaborate with multiple teams.