data analysis manager

Lunio

<div>Data Analytics Manager 
Reports To: Head of Data Science 
Job Level: Manager 
Location: UK - Hybrid 
Role Type: Full-Time, Permanent<h3 class="jobSectionHeader">
Role Purpose</h3>
Lunio helps the world's leading advertisers protect and optimise their media spend, processing and analysing billions of ad interactions. The analytics function plays a critical role in this mission, transforming large-scale data into insights that drive decision-making for both our customers and internal teams.
The Data Analytics Manager will lead the analytics function, combining hands-on analytical delivery with the coaching and development of a small team of analysts. A key focus of the role will be improving the efficiency and impact of the team through automation, AI-assisted workflows and better reporting, reducing avoidable reactive work and creating capacity for higher-value analysis, while fostering a collaborative culture that supports growth, ownership and high-quality delivery.<h3 class="jobSectionHeader">
Key Responsibilities</h3><ul><li>Team Leadership &amp; Development: Coach, and mentor a team of 2 data analysts, fostering a positive culture where people feel supported and motivated to grow.</li><li>Data Service Delivery: Own the day-to-day operation of the analytics service, ensuring requests are effectively triaged, prioritised and delivered to a high standard. Maintain clear workflows and visibility through Jira, enabling effective planning and communication of progress.</li><li>Hands-On Analytics &amp; Reporting: Contribute directly to analysis, reporting, dashboard development and experimentation, delivering high-quality analytical outputs that support decision-making across the business. Ensure dashboards and reporting solutions remain accurate, relevant and aligned to stakeholder needs.</li><li>Stakeholder Partnership: Build strong relationships across the business, translating stakeholder needs into analytical solutions, managing expectations, and promoting data-driven decision making.</li><li>Automation &amp; Continuous Improvement: Identify opportunities to automate repetitive analytical workflows and leverage AI-assisted tooling to improve team efficiency, scalability and impact. Work closely with Data Science and Engineering teams to deliver larger automation and tooling initiatives where appropriate.</li></ul><h3 class="jobSectionHeader">
Skills</h3>
SQL &amp; Python
Strong SQL and Python skills with the ability to work independently on complex analytical problems and large datasets in cloud data warehouses (e.g. AWS Redshift, Databricks etc.)
Dashboarding &amp; Reporting
Strong experience building and maintaining dashboards in BI tools such as QuickSight, Looker, Tableau, or Power BI.
Statistics &amp; Experimentation
Solid understanding of statistical concepts (i.e. A/B testing, regression analysis, and experimental design).
Automation &amp; AI Tooling
Curious and pragmatic about AI-assisted tooling, has practical experience embedding it to free up analyst time by automating repetitive workflows, not just experimenting.
Stakeholders Management
Proven ability to manage competing priorities, triage requests, and communicate effectively with stakeholders across the business, and push back when needed. Comfortable operating ticketing systems such as Jira, managing expectations, and ensuring work is delivered consistently and at a high standard establishing clear SLAs
Analytical Communication &amp; Storytelling
Able to turn data into compelling and actionable narratives. Thinks beyond the obvious metrics, identifies meaningful insights and alternative perspectives, and helps stakeholders understand what actions to take.<h3 class="jobSectionHeader">
Behaviours</h3>
Autonomy
Takes ownership of problems from identification through to resolution. Comfortable making decisions independently, seeking guidance when appropriate, and ensuring work progresses reliably.
Complexity
Able to structure ambiguous business questions, break down complex problems into manageable components, and apply sound analytical thinking to reach practical conclusions.
Influence
Builds trusted relationships across the business, communicates insights clearly, manages expectations effectively, and uses data to support decision-making and drive action.
Growth Mindset
Actively seeks opportunities to improve or automate processes, develop new skills, and adopt better ways of working. Encourages learning, experimentation, and continuous improvement within the team.<h2 class="jobSectionHeader">
Success Metrics</h2>
In your first 6 to 12 months, we would expect to see:<ul><li>Strengthen the analytics service with clear prioritisation, effective triage processes, strong visibility of work, and consistently high-quality delivery.</li><li>Build strong relationships with stakeholders across the business, becoming a trusted partner who provides timely, actionable insights and manages expectations effectively.</li><li>Identify and implement automation and AI-assisted workflows that reduce manual effort, improve delivery speed, and increase the team's capacity for higher-value analytical work.</li><li>Evolve the reporting framework to better connect business objectives to meaningful metrics. Give stakeholders confidence in the metrics they use, visibility into performance, and early warning signals when performance is at risk, with clear recommendations and follow-up actions when metrics move off track.</li><li>Create a supportive and accountable team environment, helping analysts develop their skills, grow in confidence and deliver high-quality work.</li></ul>
We're committed to building a diverse and inclusive team where people feel valued, supported and able to do their best work. We welcome applications from people of all backgrounds and experiences, and recognise that great candidates don't always meet every requirement listed in a job description. If you're excited about the role and believe you could make a positive impact at Lunio, we'd encourage you to apply.</div>

Data Analytics Manager

AAR Enterprises

Position OverviewWe are looking for a tech-savvy *Data Analysis Admin* to optimize project administration and reporting workflows for our Oil &amp; Gas contract. This role is designed for a data professional who bridges the gap between traditional project administration and cutting-edge automation. You will handle massive datasets, track project KPIs, and utilize advanced AI tools to streamline documentation and reporting.Key Responsibilities* *Advanced Data Management:* Build, maintain, and audit complex Excel models to track project progress, man-hours, procurement pipelines, and cost controls.* *AI Integration &amp; Automation:* Deploy and manage *Agentic AI tools* (e.g., AI agents, autonomous workflows, custom LLM prompts) to automate repetitive administrative tasks, summarize technical documents, and flag project anomalies.* *Reporting &amp; Dashboards:* Transform raw project data into actionable insights, creating weekly/monthly executive dashboards and KPIs for project leadership.* *Document Control Assistance:* Assist in auditing project document registers, ensuring metadata is accurate and easily retrievable using automated parsing tools.* *Process Optimization:* Continuously look for ways to reduce manual data-entry errors by scripting or leveraging modern AI productivity suites.Requirements &amp; Qualifications* *Education:* Bachelor&rsquo;s degree in Business Administration, Data Science, Information Technology, or a related field.* *Experience:* 3&ndash;5 years of administrative or data-centric experience, ideally within an industrial, engineering, or Oil &amp; Gas environment.* *Excel Expertise:* *Expert-level proficiency in MS Excel* (Power Query, Pivot Tables, advanced formulas like XLOOKUP/INDEX-MATCH, and VBA/Macros).* *AI Technical Skill:* *Advanced experience with Agentic AI tools* and workflows (e.g. AI automation agents like Zapier/Make with OpenAI/Anthropic APIs, or enterprise AI assistants).* *Skills:* Analytical mindset, high attention to detail, strong communication skills, and the ability to interpret technical engineering terminology.Work Location: In person

Data Analysis Admin

TSP LLC

<div>The Opportunity
TSPi is seeking a Data Scientist Manager with experience leading teams supporting federal data science and analytics programs. TSPi excels in meeting the needs of our partners (clients) by offering advanced technology solutions utilizing our industry-specific knowledge, iterative Agile approach, commitment and passion to serve, collaborative and fun team atmosphere, and pride in our work.
The successful candidate will lead teams of data scientists, data analysts, and other technical staff supporting data-intensive federal government projects. Projects may include work involving healthcare, social science, public health, and other federal program data. This individual will be responsible for managing analytics delivery, overseeing data management, data science, and analytical activities, supporting client engagements, and ensuring the production of high-quality data products and actionable insights.
The ideal candidate combines strong technical expertise in data analytics and data science with demonstrated experience leading project teams, managing project execution, and embracing emerging technologies, including artificial intelligence and machine learning capabilities, to improve analytical outcomes and operational efficiency.
The candidate will also be responsible for managing a team of data scientists, analysts, and engineers administratively and engaging in one-on-one meetings to provide mentorship, monitor performance and utilization, and nurture career growth. They will also be responsible for recruitment efforts to expand the overall data science and analytics team to support business growth.
Core Responsibilities<ul><li>
Implement and promote the adoption and effective use of artificial intelligence, LLMs, machine learning, automation tools, and emerging analytical technologies.</li><li>
Oversee the analysis, visualization, and interpretation of various federal datasets.</li><li>
Manage delivery of analytical products, reports, dashboards, and data-driven recommendations to clients and stakeholders.</li><li>
Provide leadership across the data lifecycle, including data intake, storage, governance, synthesis, automation, and analytical development.</li><li>
Establish and implement policies, processes, and procedures that support effective data management, analytics delivery, and team performance.</li><li>
Lead the development and implementation of QA/QC protocols, defect tracking processes, and data governance standards to ensure data quality, integrity, security, and availability.</li><li>
Serve as the primary technical and operational point of contact for clients, stakeholders, and project leadership.</li><li>
Manage project priorities, resource allocation, staffing, workload balancing, and delivery schedules to ensure successful project outcomes.</li><li>
Lead and manage teams of data analysts, data scientists, data engineers, and other technical staff across multiple projects and workstreams.</li><li>
Mentor, coach, and develop team members, providing technical guidance, performance feedback, and career development support.</li><li>
Evaluate AI-enabled tools and methodologies to improve data processing, coding efficiency, workflow automation, and analytical capabilities.</li><li>
Support proposal development, technical solutioning, project planning, and business development activities.</li><li>
Collaborate with cross-functional teams including project leadership to communicate insights and translate complex analytical findings into actionable recommendations.</li><li>
Promote continuous improvement, innovation, and adoption of industry best practices across analytics and data science teams.</li></ul>
Position Requirements &amp; Preferences
Required Qualifications<ul><li>
Bachelor's degree plus 9 years of relevant experience, Master's degree plus 7 years of relevant experience, or PhD plus 4 years of relevant experience.</li><li>
Degree in a data-focused discipline such as informatics, statistics, data science, computer science, economics, social science, public health, mathematics, or a related field.</li><li>
Strong understanding of AI tools and LLMs, machine learning concepts, analytical methodologies, and emerging technologies relevant to data analytics and data science.</li><li>
Demonstrated experience leading and managing teams of data analysts, data scientists, data engineers, and other technical professionals.</li><li>
Experience managing analytics projects, contract tasks, and client-facing deliverables.</li><li>
Strong expertise in statistical, data analytics, and data management languages including SQL, Python, SAS, and/or R.</li><li>
Strong experience with cloud platforms including AWS, Azure, or GCP.</li><li>
Experience working with relational databases and modern data management platforms including Databricks and Snowflake as well as with associated technologies including Docker, Kubernetes, MLFlow, or similar platforms.</li><li>
Experience implementing data governance, QA/QC, and data lifecycle management practices.</li><li>
Stay current on emerging trends, technologies, and best practices in data science, machine learning, and artificial intelligence and apply these learnings to project work and employee mentorship.</li><li>
Experience evaluating and implementing AI-enabled processes, automation tools, and analytical efficiencies including understanding the pros and cons of various AI LLMs.</li><li>
Experience working in a consulting environment, including direct client engagement and stakeholder communication.</li><li>
Strong technical writing skills with the ability to produce clear, concise, and well-documented analyses, reports, and presentations.</li><li>
Critical thinker with strong leadership, communication, collaboration, and problem-solving skills.</li><li>
Experience supporting proposal efforts, technical solutioning, and business development activities.</li><li>
Ability to obtain and maintain public trust access for federal information systems and successfully complete a federal background check.</li></ul>
Preferred Qualifications<ul><li>
Experience managing federal data and analytics programs particularly for CMS contracts.</li><li>
Experience with data linking methodologies, including fuzzy matching techniques such as Levenshtein distance, Jaccard similarity index, and Jaro-Winkler similarity index.</li><li>
Proficiency with version control tools including Git, Bitbucket, and SourceTree.</li><li>
Proficiency with agile project management principles and tools, including Jira and Confluence.</li><li>
Experience with leading analytic code translation and modernization efforts from SAS to Python including code evaluation and refactoring.</li><li>
Experience developing reports and dashboards, reporting solutions, workflow automation, and integrated data products.</li><li>
Experience supporting data science, predictive analytics, machine learning, or AI-enabled initiatives.</li><li>
Experience managing multidisciplinary teams in Agile project environments.</li></ul></div>

Data Scientist Manager

Confidential Government

<div>
 
 We are seeking a skilled
 
 Data Analytics Manager
 
 to lead our data analytics team, driving insights and supporting data-driven decision-making across the organization.
 
 
 
 
 
 
 Key Responsibilities:
 
 
 
 
 
 <ul>
 <li>
 Lead and manage the data analytics team to deliver actionable insights.
 </li>
 <li>
 Design, implement, and maintain data models, dashboards, and reporting tools.
 </li>
 <li>
 Collaborate with business units to understand analytics needs and translate them into solutions.
 </li>
 <li>
 Analyze complex datasets to identify trends, patterns, and opportunities.
 </li>
 <li>
 Ensure data quality, integrity, and governance across analytics initiatives.
 </li>
 <li>
 Present insights and recommendations to senior management to support strategic decisions.
 </li>
 </ul>
 
 
 
 
 
 Requirements:
 
 
 
 
 
 <ul>
 <li>
 Bachelor&rsquo;s degree in data science, Statistics, Computer Science, or a related field (master&rsquo;s preferred).
 </li>
 <li>
 7+ years of experience in data analytics, with at least 3 years in a managerial role.
 </li>
 <li>
 Strong knowledge of data visualization tools (e.g., Power BI, Tableau) and analytics platforms.
 </li>
 <li>
 Proficiency in SQL, Python, R, or similar analytics languages.
 </li>
 <li>
 Excellent leadership, communication, and problem-solving skills.
 </li>
 </ul>
</div>

Compare The Market

<div>Data Science Manager
Function: Data &amp; AI Solutions
 
Location: Hybrid, London or Peterborough office 
Curious about what&rsquo;s next?
 
So are we. Join Compare the Market and help to make financial decision making a breeze for millions.
At Compare the Market, we&rsquo;re a purpose-driven business powered by tech and AI. We&rsquo;re building high-performing, results-driven teams with the skills, mindset, and ambition to deliver outcomes at pace. Every role here plays a part in driving our mission forward, and we create an environment where you can bring your authentic self, grow a truly characterful career, and see the direct impact of your work on the lives of our customers.
We&rsquo;ve carved a meerkat-shaped niche and we&rsquo;re looking for ambitious, curious thinkers who thrive in a fast-moving, high-impact environment. If you love accountability, embrace challenge, and want to make a real difference, you&rsquo;ll fit right in. 
We&rsquo;d love you to be part of our journey.
Compare the Market is at an inflection point. We are shifting from a business that answers data questions to one that builds the intelligence powering our AI systems and platform.
As a Data Science Manager in our Data &amp; AI Solutions team, you will lead a team building the models and pipelines that sit at the heart of that platform. Depending on the domain, that might mean understanding in near real-time how hundreds of insurance partners are pricing risk across millions of customer segments, predicting which of our 34 million customers is about to need a better deal, or building the models that power personalisation in our app. These are problems where the answer does not exist in the data yet; your team builds the systems to find it.
You will set technical direction, develop your team, and work closely with product, commercial, and engineering colleagues to ensure the intelligence your team builds has a real effect on the business. 
Some of the great things you'll be doing:
Building Intelligence for Our AI Platform
<ul><li>Lead your team in building predictive systems that run continuously - always-on models that surface signals and feed our AI platform
</li><li>Design and oversee automated workflows that take model outputs through to decisions and actions
</li><li>Shape how your team approaches AI-powered systems, including where LLMs, retrieval-augmented generation, and multi-step AI patterns add value
</li><li>Ensure every model your team ships connects to a real outcome and has a mechanism to improve over time
</li></ul>Technical Leadership
<ul><li>Set the standard for modelling quality, reproducibility and production-readiness across your team - including model monitoring, drift detection and retraining cycles
</li><li>Take ownership of model performance in production: knowing when a system is degrading and having a plan to address it
</li><li>Be hands-on in design sessions, code reviews, and architectural decisions where your input matters
</li><li>Guide your team through a fast-moving tooling landscape: knowing when a classical model is the right call, when an LLM adds value, and when a more orchestrated approach is needed
</li><li>Champion responsible, auditable AI - particularly important in a regulated financial services environment where precision and explainability are non-negotiable
</li><li>Encourage and model the use of AI-assisted development tools within your team, and be actively curious about how automated coding and workflow tools can increase the pace and quality of your team's output
</li></ul>Stakeholder Partnership
<ul><li>Work closely with commercial, product, and engineering leads to translate strategic priorities into well-scoped data science work
</li><li>Present model outputs in terms of decisions and outcomes, and contribute a credible data science perspective to planning and prioritisation conversations
</li></ul>Growing Your Team
<ul><li>Develop your data scientists through regular feedback, technical mentorship, and honest career conversations
</li><li>Contribute to hiring, helping bring in people who combine technical rigour with curiosity and commercial awareness
</li>Contribute to standards and practices across the wider Data &amp; AI Solutions chapter 
<li>
</li></ul>What we'd like to see from you:
The Essentials
<ul><li>Experience leading data science teams and delivering ML solutions that run in production
</li><li>Strong Python and modelling fundamentals, sufficient to assess your team's work and contribute directly when needed
</li><li>A track record of taking models beyond the development environment and connecting them to decisions, workflows, or products with a measurable effect
</li><li>Direct experience of model production responsibilities: monitoring, degradation, retraining, and lifecycle management
</li><li>Clear communication; able to make technical work legible to commercial and product audiences
</li>Experience with MLflow, model registries, Databricks, or similar ML lifecycle and platform tooling 
<li>
</li></ul>Highly Valued
<ul><li>Hands-on experience with LLM-based systems: prompt engineering, RAG, tool use, or orchestration frameworks such as LangGraph or LangChain
</li><li>Familiarity with multi-step AI patterns, building systems where models plan, retrieve information, and take sequences of actions
</li>Understanding of experimentation at scale and the infrastructure needed to run it well 
<li>
</li></ul>Why Compare the Market?
We&rsquo;re a business built for pace and performance. Here, you&rsquo;ll be encouraged to think differently, act boldly, and deliver brilliantly in a culture that values results and rewards progress.
We believe diverse teams make better decisions, and we&rsquo;re committed to creating an inclusive workplace where everyone feels empowered to grow, contribute, and thrive.
If you&rsquo;re ready to stretch yourself, raise the bar, and grow with a team that&rsquo;s serious about performance, innovation, and purpose, we&rsquo;d love to hear from you.</div>

Data Science Manager

Waters

<div>Overview: Come help us transform Waters Corporation Transformation at Waters Corporation (NYSE: WAT) is driving the next phase of enterprise evolution. Our mission is to accelerate integration, execution, and value capture while transforming the capabilities that power our business. As part of this journey, we are building the data and analytics foundations required to enable integration, enterprise transparency, and advanced technologies such as AI-driven and predicative analytics capabilities. These capabilities support data‑driven decision‑making across the enterprise, enabling better insights, improved processes, and more efficient operations. This is a unique opportunity to join a team at the center of Waters&rsquo; transformation, working on high‑impact initiatives that shape how leaders across the company understand performance and make decisions. Typical tasks of the position include, but are not limited to:
<div>
The Manager, Business Insights and their team operate at the intersection of business strategy, analytics, and technology. This role acts as the product owner for enterprise analytics and insight offerings, defining the vision, roadmap, and success measures for how data is translated into actionable insights.</div><div> 
You will partner closely with business leaders, data engineers, analysts, and product teams to ensure analytics solutions are business‑relevant, scalable, trusted, and outcome‑driven. While not a pure hands‑on engineering role, this position requires strong technical acumen to influence solution design, challenge assumptions, and ensure analytical rigor.</div><div></div><div> 
Analytics Product Ownership &amp; Strategy</div><ul><li>
Own the vision and roadmap for business intelligence and insights across key enterprise domains (e.g., transformation, value capture, sustainability, sales &amp; orders, and operations).</li><li>
Translate business strategy and leadership questions into clear analytical problems, metrics, and products.</li><li>
Lead a Data Engineering and Analytics team to ensure data models, pipelines, and semantic layers support analytical needs.</li><li>
Prioritize initiatives based on business impact, feasibility, and strategic alignment.</li><li>
Define success criteria and adoption measures for analytics products and dashboards.</li></ul><div> 
Business Partnership &amp; Insight Delivery</div><ul><li>
Lead the definition of KPIs, scorecards, and insight narratives that connect operational data to business outcomes.</li><li>
Act as a trusted thought partner to senior stakeholders, helping them interpret data, challenge narratives, and drive fact‑based decisions.</li><li>
Synthesize complex data into clear, executive‑ready insights and recommendations.</li><li>
Drive alignment across functions on metric definitions, assumptions, and interpretation.</li><li>
Provide technical guidance and oversight on solution design, data quality, and scalability.</li><li>
Champion best practices in metric design, documentation, and reuse.</li></ul> 
<div></div>
The successful candidate will have a combination of knowledge, skills, and experience that would include the following:
<div>
Required Qualifications</div><ul><li>
Bachelor&rsquo;s degree in a quantitative or business discipline (e.g., Business Analytics, Economics, Engineering, Computer Science)</li><li>
8+ years of proven experience in Business Intelligence, analytics product ownership, or insight leadership in a complex enterprise environment.</li><li>
Strong technical literacy in data and analytics, including:
</li><li><ul><li>Data modeling and KPI design</li><li>
Advanced SQL and analytics concepts</li><li>
Understanding of modern data platforms and pipelines (even if not hands‑on)</li></ul></li><li>
Demonstrated ability to define analytical vision and translate it into delivered outcomes.</li><li>
Experience with process‑oriented analytics or process mining platform/s (e.g., Celonis, and/or PowerBI, and/or Tableau) and event‑based datasets</li><li>
Experience partnering with senior business stakeholders (VP-level and above) and influencing decisions through data.</li><li>
Experience leading and managing teams aligned to customer insights and data analytics. Must have excellent communication skills and ability to engage both deeply technical teams and non‑technical leaders.</li><li>
Ability to work onsite at Milford MA , Tuesday to Thursday , remote Monday and Friday.</li><li>
US Citizen or Permanent resident preferred.</li></ul><div>
Nice to Have / Plus Qualifications</div><ul><li>
Strong business domain expertise in enterprise systems such as:
</li><li><ul><li>SAP (orders, supply chain, finance, pricing, revenue)</li><li>
Salesforce or other commercial / service platforms</li></ul></li><li>
Experience supporting or driving enterprise transformations, integrations, or large‑scale metric standardization.</li><li>
Exposure to advanced analytics, automation, or AI‑enabled insight use cases.</li></ul>
Company Description:
<div>
Waters Corporation (NYSE:WAT) is a global leader in life sciences and diagnostics, dedicated to accelerating the benefits of pioneering science through analytical technologies, informatics, and service. With a focus on regulated, high-volume testing environments, our innovative portfolio harnesses deep scientific expertise across chemistry, physics, and biology. We collaborate with customers around the world to advance the release of effective, high-quality medicines, ensure the safety of food and water, and drive better patient outcomes by detecting diseases earlier, managing routine infections, and combating antibiotic resistance. Through a shared culture of relentless innovation, our passionate team of ~16,000 colleagues turn scientific challenges into breakthroughs that improve lives worldwide.</div><div></div><div> 
Diversity and inclusion are fundamental to our core values at Waters Corporation. It benefits our employees, our products, our customers and our community. Waters complies with all applicable federal, state, and local laws. Qualified applicants are considered without regard to sex, race, color, ancestry, national origin, citizenship status, religion, age, marital status (including civil unions), military service, veteran status, pregnancy (including childbirth and related medical conditions), genetic information, sexual orientation, gender identity, legally recognized disability, domestic violence victim status, or any other characteristic protected by law. Waters is proud to be an equal opportunity workplace and is an affirmative action employer. All hiring decisions are based solely on qualifications, merit, and business needs at the time.</div></div>

Data Analytics Manager - Business Insights - Milford MA - Hybrid

JMAN Group

<div>JMAN is the commercial data partner that specializes in maximizing value creation activities for private equity funds and their portfolio companies. We partner with our clients to address the growing need for investment decisions and value creation initiatives to be backed by reliable, real-time data. When companies partner with JMAN, we combine our data science and data engineering expertise with our deep commercial understanding to deliver tangible, high-value outcomes at pace. Founded in 2010, JMAN has a global footprint with offices in New York, London and Chennai. Our team of more than 350 experts partner with more than 80 private equity funds and over 200 portfolio companies. Nearly 85% of our business is from recurring partnerships with our clients. JMAN has been a portfolio company of Baird Capital since 2023. 
 
<h2 class="jobSectionHeader">Position:
</h2>We are a rapidly scaling business focused on delivering applied data science solutions that create measurable commercial value. While we work across a range of AI paradigms, data science sits at the core of what we do, and we are looking for individuals with deep, proven expertise in this area. 
This is a technical delivery leadership role for a highly experienced Data Scientist who leads with structured problem solving and client empathy. The primary measure of success is whether clients achieve meaningful business outcomes through robust, well-designed data science solutions, not the adoption of the latest AI trends. 
You will own the full lifecycle of data science engagements: shaping ambiguous problems, designing and delivering statistical and machine learning models, and ensuring they are embedded into operational workflows. You will work across organisations at every stage of data maturity, applying sound judgement to determine what is feasible, practical, and commercially valuable. 
While the role may involve exposure to Generative AI and autonomous AI, these are not substitutes for strong data science fundamentals. Candidates must demonstrate deep, hands-on experience delivering applied machine learning and statistical modelling in real-world settings.
Internally, you will act as a data science standard-setter, helping define best practice, raising the quality bar, and developing others within the team. 
Scope of Work
Our work spans multiple AI paradigms, with a clear emphasis on Data Science as the primary discipline for this role:<ul><li>
Data Science (Primary Focus):</li><li>
Statistical modelling, machine learning, predictive analytics, and decision science delivered into production environments and real business processes.</li><li>
Generative AI (Secondary):</li><li>
LLM-powered applications such as RAG pipelines and document intelligence, applied where appropriate to support data-led solutions.</li><li>
Autonomous AI (Emerging):</li><li>
Agent-based systems and AI workflows, used selectively where they add clear value.</li></ul> 
~75&ndash;80% of the role is focused on Data Science-led delivery, including problem structuring, model development, evaluation, and operationalisation. The remaining time is spent on client engagement, team leadership, and broader AI exposure where relevant. 
Core Responsibilities<ul><li>
Own end-to-end delivery of data science workstreams, from problem definition through to production deployment and ongoing monitoring.</li><li>
Translate ambiguous business problems into hypothesis-driven data science solutions, grounded in statistical rigour and practical feasibility.</li><li>
Lead the design and deployment of machine learning models, ensuring they are robust, explainable, and operationally viable.</li><li>
Provide technical oversight across projects, with a strong focus on model quality, evaluation frameworks, and reproducibility.</li><li>
Work closely with data engineers to ensure models are effectively integrated into production systems, with appropriate pipelines, monitoring, and lifecycle management.</li><li>
Apply sound judgement in selecting modelling approaches, balancing sophistication with interpretability, maintainability, and business value.</li><li>
Act as a trusted advisor to clients, communicating complex data science concepts clearly and influencing decision-making at senior levels.</li><li>
Manage delivery timelines, risks, and priorities across engagements.</li><li>
Set the standard for data science excellence, including coding standards, documentation, and best practices.</li><li>
Mentor junior team members, supporting their development as data scientists.</li></ul> 
The most important requirement for this role is proven, hands-on experience in Data Science. Candidates must be able to demonstrate a strong track record of delivering end-to-end machine learning or statistical solutions in real-world environments.<h2 class="jobSectionHeader"> 
Requirements:
</h2><ul><li>5+ years&rsquo; experience in Data Science or applied machine learning, ideally in consulting, high-growth, or commercial environments.</li><li>
Strong applied machine learning expertise, including:Model selection and developmentFeature engineeringEvaluation and validationDeployment into production environments</li><li>
Demonstrated experience taking models beyond experimentation into operational, business-critical systems.</li><li>
Strong background in statistics and quantitative problem solving.</li><li>
Proficiency in Python and SQL, with experience writing production-quality, maintainable code.</li><li>
Experience with modern data science tooling, including:Version control (Git)Cloud platforms (AWS, GCP, or Azure)Experiment tracking and model managementWorkflow orchestration and containerisation</li><li>
Strong understanding of MLOps principles, including model monitoring, retraining, and lifecycle management.</li><li>
Proven ability to translate business problems into data science solutions that deliver measurable outcomes.</li></ul>
Beneficial<ul><li>
Exposure to Generative AI (e.g. LLMs, RAG) is beneficial but not a substitute for core data science expertise.</li><li>
Awareness of emerging AI paradigms (e.g. agent-based systems) is a plus, but not required.</li></ul> 
Specialisms (Data Science&ndash;led)
We particularly value depth in applied data science areas such as:<ul><li>
Predictive Modelling &amp; Forecasting</li><li>
Customer analytics (segmentation, churn, LTV)</li><li>
Pricing and optimisation models</li><li>
Time series modelling</li><li>
Experimental design and causal inference</li><li>
Natural Language Processing (within a traditional ML framework as well as LLM-based approaches)</li></ul><h2 class="jobSectionHeader"> 
Other information:
</h2>If you feel that you would be a strong addition to our team, but you do not fully meet all the requirements above, we would like to encourage you to please apply anyway. As we expand, we are looking for individuals across all levels and maybe able to discuss a suitable alternative with you.
JMAN is committed to equal employment opportunities. We are a diverse, high performing team and base all our employment decisions on merit, job requirements and business needs.<h2 class="jobSectionHeader"> 
Other information</h2><ul><li>
Discretionary bonus &ndash; based on personal and company performance</li><li>
25 days annual leave + bank holidays</li><li>
Pension with a company contribution up to 8%</li><li>
Health Insurance from day 1</li><li>
Life insurance and long-term disability insurance</li><li>
Market-leading parental leave policy</li><li>
Salary Sacrifice Nursery Scheme through YellowNest</li><li>
Salary Sacrifice EV Scheme with Octopus Vehicles</li><li>
Additional Health Cash Plan with MediCash</li><li>
Cycle to work scheme</li><li>
Referral bonus for bringing in new JMAN hires</li><li>
Extensive training and coaching opportunities</li><li>
Regular company socials and retreats</li><li>
Hybrid working - minimum of 3 days in the office (E3N)</li></ul></div>

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Data Analytics Manager - Business Insights - Milford MA - Hybrid

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