Data Science Manager

3 months ago

London, Greater London, United Kingdom Concirrus Full time
Data Science Manager

Concirrus

We are the leading data and analytics platform for specialty and commercial insurance globally.

Our mission is to revolutionise the insurance industry by simplifying and streamlining insurance operations with cutting-edge technology. We have been focused on the risk management and pricing parts of the market but we're now expanding our focus.

D&I Statement

We aspire to build a diverse team and cultivate an inclusive environment where everyone is empowered to perform their best work. As we continue to learn and evolve, we are committed to:
  • Providing a safe environment where all individuals feel accepted and valued.
  • Continuing to educate ourselves and celebrate our differences.
  • Ensuring that our behaviors align with our values and our dedication to DE&I.
  • Regularly reviewing our performance and perpetually striving for improvement.
The Role

We are seeking an experienced and highly skilled Data Science Manager to lead our team of Data Scientists. In this role, you will be responsible for overseeing the end-to-end Data Science and Machine Learning Modeling processes, including data ingestion, feature creation and selection, cross-validation, hyperparameter tuning and model assessment to model deployment, to support our teams in solving complex business problems for our clients in the commercial insurance, brokerage, and reinsurance industries.

Responsibilities

Team Leadership:
  • Lead and mentor the Data Science team, ensuring they follow best practices, adhere to quality standards, and deliver consistent and timely results.
  • Develop and implement robust data science and modeling architectures, pipelines, and processes to build linear and nonlinear models efficiently and effectively.
  • Foster a culture of innovation, encouraging the team to explore and adopt new technologies and methodologies to stay ahead of industry trends.
  • Manage the data science project lifecycle, including planning, execution, monitoring, and delivery.
  • Lead by example when it comes to our leadership principles or Data Science/ML expertise.
  • Develop and report on key KPIs within Data Science that drive the success of the business.
Stakeholder Collaboration:
  • Collaborate with our Product and Commercial leaders to develop compelling offerings that drive revenue and customer benefits.
  • Work closely with Engineering team to make sure that output of Data Science teamwork can be injected into our product offerings.
  • Be comfortable in front of customers and instill confidence with your ability to understand customer needs and convey complex concepts in a simple manner.
  • Engage with key stakeholders, including executives, to communicate Data Science strategy, progress, and results.
  • Be an authoritative voice within the business to represent the needs of the market and the value that our products can offer.
Technical Skills and Qualifications
  • Machine Learning Expertise: Deep understanding of machine learning algorithms, principles, and their application.
  • Insurance Risk Modelling Expertise: Deep understanding of insurance risk models, actuarial science, and the ability to apply statistical and machine learning techniques to assess and predict risk in the insurance domain.
  • Insurance Domain Expertise: In-depth understanding of the insurance sector. Ability to leverage this expertise to drive data-driven decision-making and to develop models that reflect the nuances of insurance risk and customer behavior.
  • Strong data wrangling and processing skills along with a background in analysis and predictive modelling.
  • Extensive experience with supervised classification and regression modelling using linear and nonlinear techniques.
  • Knowledge of the full end-to-end modelling lifecycle from feature creation, selection, model-building, hyperparameter optimisation and model assessment.
  • Experience and familiarity with the tools and tech stack being used by team such as Python, Apache Spark (preferably with PySpark) and Python pandas, numpy, scikit-learn, Supervised Learning (Regression, Classification), Unsupervised (Clustering), Dimensionality Reduction, Model Selection and Optimisation, Feature Selection, Metric Selection, Bootstrapping, Ensembling & Stacking Methods.
  • Exposure with various GEN AI models (LLMs) would be an added advantage.
Personality Traits and Mindset
  • Strong sense of urgency and ability to work under pressure to meet tight deadlines.
  • Ability to thrive in ambiguous situations and make decisions with incomplete information.
  • Self-motivated and able to operate with complete self-agency.
  • Passionate about data engineering and committed to delivering high-quality work.
  • Thought leader in the data Science domain, with a deep understanding of industry trends and best practices.
  • Ability to inspire and motivate the team towards continuous improvement and innovation.
Benefits

As well as the opportunity to work in a fast-paced, dynamic environment, we like to look after our team members at Concirrus. Here are some of our perks...
  • We pay competitively with regular pay reviews.
  • Tax efficient Pension Scheme with 5% matched contribution.
  • Private medical insurance from Vitality Healthcare.
  • Life insurance AIG Life.
  • Learning & Development fund for all employees.
  • 25 days annual leave (plus public holidays).
  • Modern offices close to Liverpool Street Station.
  • Coffee and snacks are all on hand in the office to keep you fueled.
  • Monthly team drinks, birthday cakes and social events.
  • Season Ticket Loan and Cycle2Work schemes, plus seasonal flu vaccinations.
  • Plus, we're always on the lookout for creative ways to look after our employees and encourage them to come to us when they have an idea or need.
Join us at Concirrus and be part of a diverse and inclusive team where your talents and ideas are valued. Apply now and let's transform the insurance industry together

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