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Freelance Behavioural Science Consultant

Contract: 6-week initial engagement (potential for extension)
Location: Remote, with occasional in-person workshops as required
Rate: £300-£400 per day (outside IR35)

About the Role

We’re seeking a Freelance Behavioural Science Consultant to apply behavioural insights to real-world business challenges, shaping strategy and driving meaningful customer engagement.

You’ll bring together psychology, behavioural economics, and data-driven insight to help design interventions that influence decision-making and improve outcomes – from enhancing loyalty programs to optimising customer experiences.

Key Responsibilities

• Prepare, facilitate, and deliver interactive workshops.

• Conduct and synthesise academic literature reviews (e.g., psychology of tiering, motivation, and reward).

• Lead qualitative and quantitative research, including desk and primary consumer studies.

• Analyse behavioural data and cultural insights to uncover drivers of decision-making.

• Translate findings into creative, evidence-based behavioural strategies.

• Keep up to date with new developments in behavioural science and emerging applications.

• Collaborate effectively with project teams, providing guidance, delegation, and feedback as needed.

About You

You combine academic depth with commercial creativity, using behavioural theory to deliver actionable and measurable change.

Key Skills & Attributes:

• Strong grasp of behaviour change principles, heuristics, and cognitive biases.

• Proficient in research design, analysis, and experimental methodology.

• Excellent communication – written, visual, and verbal.

• Analytical, strategic, and detail-oriented, with strong organisational skills.

• Skilled in Microsoft Excel and PowerPoint.

• Able to balance multiple projects and deadlines under pressure.

• Commercially minded with strong problem-solving ability.

Preferred Background:

• 4-6 years’ experience in consulting, behavioural science, or client-side strategy roles.

• Degree in Psychology, Behavioural Economics, or a related discipline.

• Experience in retail, loyalty, or consumer engagement is highly advantageous.

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Data Scientist / Software Engineer (AI)

Lead Software Engineer (AI) position having experience in classic and generative AI techniques, and responsible for design, implementation, and support of Python based applications.

What you’ll do:?

• Deliver client engagements that use AI rapidly, on the order of a few weeks
• Stay on top of current tools, techniques, and frameworks to be able to use and advise clients on them
• Build proofs of concept rapidly, to learn and adapt to changing market needs
• Support building internal applications for use by associates to improve productivity

What you’ll need:
7+ years of experience in classic AI techniques and at least 1.5 years in generative AI techniques. Demonstrated ability to run short development cycles and solid grasp of building software in a collaborative team setting.

Must have:

• Experience building applications for knowledge search and summarization, frameworks to evaluate and compare performance of different GenAI techniques, measuring and improving accuracy and helpfulness of generative responses, implementing observability.
• Experience with agentic AI frameworks, RAG, embedding models, vector DBs
• Experience working with Python libraries like Pandas, Scikit-Learn, Numpy, and Scipy is required.
• Experience deploying applications to cloud platforms such as Azure and AWS.
• Familiarity with AWS Bedrock / Azure AI / Databricks Services.
• Solid grasp of building software in a collaborative team setting – use of agile scrum and tools like Jira / GitHub.
• Demonstrated ability to run short development cycle.
• Excellent written, verbal, and interpersonal communication skills with the ability to present technical information in a clear and concise manner to IT Leaders and business stakeholders.

Nice to have:

• Experience in finetuning Language models.
• Experience in MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc.,
• Experience in Machine learning models and techniques like NLP, BERT, Transformers, Deep learning.
• Experience building scalable data models and performing complex relational databases queries using SQL (Oracle, MySQL, PostgreSQL).

Who you are:

• Effective time management skills and ability to meet deadlines.
• Excellent communications skills interacting with technical and business audiences.
• Excellent organization, multitasking, and prioritization skills.
• Must possess a willingness and aptitude to embrace new technologies/ideas and master concepts rapidly.
• Intellectual curiosity, passion for technology and keeping up with new trends.
• Delivering project work on-time within budget with high quality.

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Key Responsibilities

Experiment and Develop

• Lead the end-to-end development of NLP and ML models, ensuring reproducible research, efficient experimentation, and scalable deployment.

• Apply best practices in model management, data handling, and software delivery to deliver high-quality AI solutions.

Collaborate

• Partner with cross-functional global teams to translate research into production-ready systems.

• Mentor and elevate peers by sharing best practices and technical insights.

Deliver

• Translate complex business challenges into well-scoped projects and deliver solutions efficiently in a fast-paced, agile environment.

• Ensure accountability for timely, high-impact deliverables that align with organizational priorities.

Innovate

• Explore and prototype new methods in NLP, IR, and Generative AI, leveraging emerging techniques such as transformer-based architectures, RAG frameworks, and agentic systems.

• Contribute to a culture of experimentation and continuous learning.

Inspire

• Communicate technical concepts clearly to both technical and non-technical audiences.

• Advocate for AI adoption and best practices across the enterprise through demos, presentations, and collaboration.

Basic Qualifications

• Master’s degree in a relevant field (e.g., Computer Science, Computational Linguistics, Machine Learning) or equivalent experience.

• 3+ years of hands-on experience building NLP, IR, or ML systems from ideation to deployment.

• Strong software engineering foundation and prototyping skills.

• Proven ability to translate research into impactful, production-level solutions.

• Excellent collaboration and communication skills across diverse, cross-functional teams.

• Demonstrated success applying novel IR or NLP models to real-world challenges.

• Experience thriving in fast-paced, agile environments with evolving requirements.

Technical Qualifications

• Deep understanding of classical machine learning and modern deep learning approaches for NLP (e.g., transformer architectures).

• Familiarity with large language models (LLMs) and their underlying mechanisms.

• Hands-on experience with Generative AI concepts, including prompt engineering, in-context learning, and function calling.

• Experience implementing RAG frameworks, fine-tuning or pre-training language models, and curating training data.

• Practical experience using agentic frameworks (e.g., LangGraph, AutoGen, Semantic Kernel) to build intelligent applications.

• Proficiency in Python, Git, and cloud environments such as AWS or Azure.

• Experience with lightweight UI development, rapid prototyping, and agile iteration.

Preferred Qualifications

• 5+ years of practical experience building IR, ML, or NLP systems in academia or industry.

• Background in search, question answering, or document summarization for large-scale datasets.

• Experience building AI-driven solutions for document-heavy domains (e.g., legal, financial, or compliance).

• Publication record at leading research venues (ACL, EMNLP, NAACL, NeurIPS, ICML, SIGIR, etc.).

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