Senior Consultant

JR United Kingdom; United Kingdom; On-site; GBP 60,000 - 100,000; Full time

Job summary

An innovative strategy consultancy is seeking a Senior Data Consultant to lead the design and delivery of cutting-edge data science and AI solutions. This role is pivotal in aligning technical solutions with business objectives, ensuring clients derive maximum value from their data initiatives. You will engage with clients, providing thought leadership and translating complex technical concepts into actionable insights. Join a dynamic team and be at the forefront of data-driven strategies, working collaboratively to tackle business challenges and drive impactful results.

Qualifications

• Educated to degree level in relevant fields such as Data Science or Engineering.
• Proven experience in data science, analytics, or AI fields.

Responsibilities

• Collaborate with clients to design end-to-end data solutions.
• Oversee technical delivery teams to maximize client value.

Skills

Data Science

Machine Learning

AI Solutions

Analytics

Problem-Solving

Communication Skills

Education

Degree in Data Science or related field

Degree in Engineering or Mathematics

Tools

AWS

Azure

GCP

Spark

Kafka

Job description

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Omnis Partners is delighted to be partnered with a disruptive, innovative strategy consultancy, hiring for highly commercial and strategic Senior Data Consultants with an array of expertise across the data lifecycle and a digital first mindset. You will spearhead the design, shaping and delivery of innovative data science, AI and analytics solutions for a portfolio of clients. This individual will play a pivotal role in seamlessly aligning technical solutions with business objectives, ensuring clients realise maximum value from a range of data products and solutions.

Key Responsibilities:

Solution Design & Delivery

• Collaborate with clients to understand their business challenges, objectives, and data needs.
• Design end-to-end data solutions in partnership with engineering and consulting teams, from discovery to deployment, tailored to client goals.
• Oversee technical delivery teams in delivering solutions that deliver maximum commercial impact and value return for the client.

Client Engagement & Strategy

• Act as the primary point of contact for clients during project lifecycles, ensuring clarity and alignment on deliverables from a practical and commercial perspective.
• Provide thought leadership and guidance to clients on data-driven strategies and emerging trends.
• Translate technical concepts into commercially orientated, business-focused insights and solutions, facilitating informed decision-making for stakeholders.
• Collaborate with multidisciplinary teams, including Data Architects, Developers, Data Scientists, Engineers, and Analysts, ensuring alignment with project timelines and client objectives.
• Partner with sales and business development teams to identify opportunities for upselling and expanding client engagements.

Technical Knowledge

• Oversee the design and implementation of scalable data pipelines, machine learning models, AI products and advanced analytics platforms.
• Stay abreast of industry trends, tools, and technologies to ensure solutions remain cutting-edge and competitive.
• Ensure adherence to best practices in data , ML, AI and engineering.

Experience Required:

• Educated to degree level in Data Science, Machine Learning, Physics, Chemistry, Engineering, Economics, Computer Science, Mathematics, Statistics, or a related field.
• Proven experience in data science, analytics, AI or engineering fields.
• Proven track record of successfully delivering complex data projects, with demonstrable problem-solving skills, and a focus on delivering practical, commercially impactful solutions.
• Strong commercial track record in a formal consulting environment.
• Ability to wear multiple hats; elements of pre-sales, solution architecture, product management, business analysis and ongoing consultancy to ensure client success
• Strong understanding of a range of technical programming languages and experience in machine learning frameworks, including architectural design and data platforms.
• Knowledge of cloud platforms (AWS, Azure, or GCP) and data engineering tools (e.g., Spark, Kafka).
• Exceptional communication skills, with the ability to influence technical and non-technical stakeholders alike.