Lead Data Scientist

1 month ago

United Kingdom Inara Full time

Job Title: Lead Data Scientist (Time Series & Mobility Data Analysis)
Industry: Public Sector & InsurTech

Location: London, hybrid (one day a week in the office)

An emerging technology company specialising in identifying uncharted global risks. This company leverages cutting-edge technologies to provide near-real-time monitoring and analysis of threat actor activities worldwide, delivering actionable insights across multiple domains.

We are looking for an experienced Lead Data Scientist with a deep background in time series analysis and mobility data to lead the development of advanced data science pipelines. The successful candidate will play a pivotal role in optimising and deploying models that integrate with an existing PostgreSQL-based infrastructure, enabling the identification of patterns of life (PoL), anomaly detection, and high-volume data analysis. You’ll be tasked with building scalable, efficient pipelines that meet the diverse needs of our clients, including those operating in compute-constrained environments.

Time Series Analysis & Modelling:
Design and implement advanced time series models for analysing large-scale mobility data.
Optimise models for high performance in low-resource computing environments.
Create scalable anomaly detection systems adaptable to various levels of analysis.
Data Object Generation & Analysis:
Create and manage data objects such as clusters, paths, and PoL, ensuring they are trackable, interrogable, and enrichable.
Integrate these objects into broader analytical frameworks for comprehensive data analysis.
Data-to-Text & Natural Language Query (Nice to Have):
Explore the potential of data-to-text models to generate narrative descriptions of trends and anomalies.
Contribute to building natural language query (NLQ) models for non-technical stakeholders to access data insights.

Time Series Analysis: Proven experience in developing time series models for large-scale geodata, including geo-clustering and trajectory analysis at multiple scales.
Expertise in creating models for PoL detection and anomaly identification using algorithms such as ST-DBSCAN, Dynamic Time Warping, and Trajectory Analysis.
Programming: Proficiency in Python or R, with experience using libraries like Pandas, GeoPandas, Scikit-learn, TensorFlow, and PyTorch.
NLP (Nice to Have): Experience with natural language processing, data-to-text models, and natural language query systems is a plus.
Advanced Knowledge: Familiarity with deploying Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) using knowledge graphs is desired.

Strong analytical and creative problem-solving abilities.
Ability to work effectively with multidisciplinary teams, including engineers, software developers, and SMEs.
Adaptability: Comfortable managing multiple projects in a fast-paced environment.

Master’s or PhD in Data Science, Statistics, Computer Science, or a related field.
Experience: At least 6 years of experience in data science, with a focus on time series and mobility data analysis.

Competitive salary and comprehensive benefits package, including health insurance and mental health support.
Continuous professional development and training opportunities.

Diversity and inclusion are celebrated, and we are committed to fostering an inclusive workplace for all employees.

Note: This is a senior-level position intended for candidates with significant experience in time series analysis and mobility data. If you meet these criteria, we encourage you to apply and contribute to transformative projects in the tech and defence sectors.

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