Senior Data Scientist

At Cotality, we are driven by a single mission—to make the property industry faster, smarter, and more people-centric. Cotality is the trusted source for property intelligence, with unmatched precision, depth, breadth, and insights across the entire ecosystem. Our talented team of 5,000 employees globally uses our network, scale, connectivity and technology to drive the largest asset class in the world. Join us as we work toward our vision of fueling a thriving global property ecosystem and a more resilient society.

Cotality is committed to cultivating a diverse and inclusive work culture that inspires innovation and bold thinking; it's a place where you can collaborate, feel valued, develop skills and directly impact the real estate economy. We know our people are our greatest asset. At Cotality, you can be yourself, lift people up and make an impact. By putting clients first and continuously innovating, we're working together to set the pace for unlocking new possibilities that better serve the property industry.

Job Description:

• Design and implement sophisticated machine learning algorithms and statistical models to analyse large, complex datasets and extract actionable insights.
• Develop and program advanced methods, processes, and systems to consolidate and analyse unstructured, diverse big data sources.
• Create predictive models and algorithms that generate valuable insights for client services and product enhancement.
• Collaborate with cross-functional teams to understand business requirements and translate them into analytical frameworks.
• Develop and maintain data pipelines to ensure efficient data processing and analysis.
• Create advanced visualisation tools and dashboards to communicate findings effectively to technical and non-technical stakeholders.
• Mentor junior data scientists and provide technical guidance on complex projects.
• Evaluate and implement new data science technologies and approaches to improve analytical capabilities.

Job Qualifications:

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, or related quantitative field required.
• 3+ years of relevant work experience required.
• Strong programming skills in languages such as Python, R, or Java required.
• Expertise in statistical analysis, machine learning algorithms, and predictive modeling required.
• Experience working with big data technologies and unstructured data sources required.
• Proficiency with data manipulation and analysis libraries (Pandas, NumPy, SciPy) required.
• Experience with machine learning frameworks (TensorFlow, PyTorch, scikit-learn) required.
• Excellent communication and presentation skills required.

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• Time Away: Generous paid leave, 8 bank holidays, plus dedicated days for wellbeing and volunteering.
• Family Support: Up to 16 weeks of fully paid parental leave, along with a baby bonus to help you get started.
• Health & Wellbeing: Company-paid private medical cover, with mental health and wellness resources included.
• Retirement: Pension scheme with employer contributions.
• Financial Perks: £375 annual wellbeing allowance.
• Extras: Recognition rewards, referral bonuses, exclusive discounts, and more!

Cotality's Diversity Commitment:​

Cotality is fully committed to employing a diverse workforce and creating an inclusive work environment that embraces everyone’s unique contributions, experiences and values. We offer an empowered work environment that encourages creativity, initiative and professional growth and provides a competitive salary and benefits package. ​ We are better together when we support and recognize our differences. 

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Equal Opportunity Employer Statement:​

Cotality is an Equal Opportunity employer committed to attracting and retaining the best-qualified people available, without regard to race, ancestry, place of origin, colour, ethnic origin, citizenship, creed, sex, sexual orientation, record of offences, age, marital status, family status or disability. Cotality maintains a Drug-Free Workplace. ​

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Please apply on our website for consideration.​

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