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The company:

The firm is a global consulting and analytics organization that partners with leading enterprises to deliver measurable business impact. It combines deep domain expertise with advanced data science and technology to solve complex operational and strategic challenges.

What you’ll do:

• Analyze customer support center operations through data modeling and shadowing
• Support the client’s migration to Python from legacy systems (SAS, other databases)
• Build and optimize models to improve scheduling, workflows, and customer experience
• Contribute to advanced operational research and non-linear programming in later phases
• Collaborate with stakeholders to deliver actionable, model-driven insights

What we’re looking for:

• 2-3 years of experience in data science / modeling roles
• Strong skills in Python, Pandas, NumPy, and SQL
• Exposure to operational research or customer support center/back-end operations a plus
• Hands-on experience building models (not just ETL pipelines)

If this opportunity aligns with your skills and interests, we encourage you to apply and explore the role further

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We’re looking for a Lead Data Scientist to join a fast-paced data team within a major UK retailer.

In this role, you’ll lead the development of data-driven solutions to support marketing strategy using techniques such as machine learning, causal inference, Marketing Mix Modeling (MMM), and experimental design. You’ll work closely with marketing teams and external partners to analyse customer behaviour, optimise marketing performance, and deliver impactful business recommendations.

Key Responsibilities:

• Lead end-to-end data science projects to improve marketing efficiency and ROI.
• Develop models for MMM, customer lifetime value, churn prediction, and channel attribution.
• Partner with stakeholders to design and evaluate marketing experiments.
• Create dashboards and data products for self-serve analytics and real-time insights.
• Ensure high standards in data quality, model governance, and documentation.
• Mentor and support junior team members as a technical lead

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A leading home services SaaS company is hiring a Head of Data & AI to define and scale its data strategy. This role will oversee the development of modern data platforms and AI capabilities that power customer personalization, operational efficiency, and business growth.

Responsibilities

• Build and manage a modern data stack (dbt, Snowflake, Fivetran, BI tools).
• Ingest and normalize data from multiple sources to power real-time operations and reporting.
• Partner with executives to structure data for AI-driven workflows (routing, pricing, recruiting, logistics).
• Deliver critical dashboards and unify reporting across the business.
• Lead and grow a small team of analysts and engineers.

Requirements

• 7+ years in data, analytics, or engineering, including 2+ years in leadership.
• Strong technical skills: SQL, dbt, data warehousing, BI tools.
• Experience in high-volume, operationally complex businesses (services, logistics, marketplaces).
• Passion for AI agents and their application in real operations.
• Bonus: Python skills, exposure to LLM frameworks, or background in logistics optimization.

What They Offer

• Competitive base + performance bonus.
• Remote-first culture with full benefits.
• High autonomy and direct exposure to executive leadership.

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Director of Data Science – Pricing, Lead Scoring & Personalization

Location: San Francisco (Remote Eligible)

Salary: $250-280k base + equity

We are looking for a Director of Data Science to lead a high-impact team focused on pricing optimization, lead scoring, and customer personalization for a rapidly growing travel platform backed by top investors. This role is ideal for a data science leader who can define strategy, develop predictive models, and drive measurable business impact through advanced analytics and machine learning.

Key Responsibilities:

• Lead and scale a high-performing team of data scientists and analysts, fostering a culture of experimentation, collaboration, and innovation.
• Develop dynamic pricing models that optimize revenue, improve conversion rates, and enhance market competitiveness.
• Enhance lead scoring and customer personalization by building predictive models that identify high-value leads, optimize sales funnels, and improve user experiences.
• Design and analyze A/B tests, causal inference models, and other experimentation techniques to measure and optimize product, marketing, and operational decisions.
• Establish frameworks for data quality, governance, and self-service analytics to ensure consistency and accessibility across the company.
• Collaborate with Product, Finance, Marketing, Sales, and Operations to define key business metrics, analyze performance, and provide strategic recommendations to executive leadership.

Qualifications:

• 10+ years of experience in data science or analytics, including at least 5 years in leadership roles.
• Expertise in predictive modeling, dynamic pricing, and lead scoring using machine learning and statistical methods.
• Strong experience with SQL, Python, R, and BI tools such as Looker, Tableau, or Sigma.
• Proven ability to translate data insights into business strategy and influence executive stakeholders.
• Deep knowledge of A/B testing, experimentation, and customer segmentation.
• Industry experience in B2B SaaS or travel is a strong plus.
• Bachelor’s degree in a technical field required; Master’s or MBA preferred.

This is an opportunity to shape the data science strategy at a fast-growing company, driving decisions that will transform pricing, customer engagement, and business growth.

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Job Title: Director of Data Science – Biopharma Commercial Analytics
Location: Hybrid – San Francisco Bay Area
Salary: $250-300k base + bonus + equity

Drive the Commercial Data Science Strategy for a High-Growth Digital Health Innovator

Join a mission-driven health tech company redefining how the biopharma industry uses data to drive access, adherence, and market success. This is a unique opportunity to lead the data science function at a fast-scaling, venture-backed startup and shape the next generation of commercial analytics tools and ML-powered insights.

The Role

As Director of Data Science, you’ll lead a team of Data Scientists and Analytical Data Engineers responsible for delivering impactful analytics and machine learning solutions across the commercial lifecycle. You’ll operate as a strategic partner across Product, Customer Experience, and Go-to-Market teams, influencing everything from AI product features to patient access strategies.

Key Responsibilities:

• Build, mentor, and scale a high-performing data science team with a focus on commercialization in the biopharma space
• Lead the development of predictive models and ML algorithms to solve problems in Market Access, Patient Services, and Field Force Optimization
• Own the architecture, data models, and pipelines supporting scalable advanced analytics in a multi-tenant SaaS environment
• Partner with Product and Commercial leaders to translate client needs into intelligent analytics tools and embedded insights
• Present findings and influence decisions at the VP and executive level, internally and with client stakeholders
• Ensure code quality, security, and compliance across deployed models and analytics products
• Monitor trends in commercial analytics, generative AI, and regulatory standards to drive innovation

Your Background

Required Experience:

• 7+ years in biopharma or life sciences commercial analytics, including direct experience in Market Access, Commercial Ops, or Patient Services
• Advanced expertise in machine learning techniques (e.g., regression, classification, forecasting, NLP, A/B testing) applied to real-world commercial use cases
• Proficient in Python and SQL; experience with Snowflake, dbt, and Snowpark highly valued
• Strong understanding of data sets common to biopharma (specialty pharmacy, claims, HCP targeting, CRM, etc.)
• 3+ years managing and scaling high-impact Data Science teams in high-growth or enterprise health tech environments
• Proven record of driving measurable business outcomes through ML/AI-powered solutions
• Excellent cross-functional communication skills; ability to bridge technical depth with commercial strategy
• M.S. or Ph.D. in a quantitative discipline (e.g., Data Science, Engineering, Statistics, Computer Science)

Preferred Qualifications:

• Familiarity with HIPAA, SOC2, HITRUST, or other healthcare regulatory frameworks
• Experience working in AWS-based cloud environments
• Exposure to LLMs, agentic AI frameworks, or AI-enhanced product features
• Background in specialty data integration (e.g., hub services, reimbursement workflows)

What’s On Offer

• Executive-level role shaping the analytics vision for a fast-scaling digital health company
• Competitive compensation, performance bonus, and equity in a high-growth startup
• High-impact work that directly improves patient outcomes and access
• Collaborative and mission-driven culture at the intersection of healthcare and AI
• Opportunity to influence product strategy and drive adoption of next-generation commercial analytics tools

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Lead Data Scientist
London
Private Equity
£140,000 – £150,000 + benefits

Harnham is working with a tech firm in the Private Equity space and hiring a few positions across Data Science, Machine Learning Engineering and Data Engineering.

The company have an impressive founding team and hold a strong reputation within the Data & AI and Private Equity space.

They partner with some leading investment firms in deploying AI and machine learning for the sole purpose of creating value. Often working in ambiguous and greenfield environments, you will collaborate with a strong team of technical people across multiple industries to solve complex commercial and data problems, delivering key data science initiatives that drive performance and revenue.

In this role you will lead the technical teams that deliver value.

The Role – Lead Data Scientist

You will be:

• Working on multiple engagements within portfolio companies across various different industry sectors
• Delivering key Data Science / AI initiatives that drive value for customers.
• Shaping how projects are delivered, driving performance and working closely with C-level execs.
• Providing technical leadership across the business, with a focus on end-to-end machine learning solutions.

Experience – Lead Data Scientist

You will have:

• An M.Sc. or Ph.D. in: Machine Learning, Statistics, Applied Mathematics, Computer Science, Engineering, etc.
• Experience using Python is a must
• Knowledge of cloud technologies important (agnostic)
• A strong knowledge of statistical/machine learning models applied to real-world problems
• A keen interest in problem-solving and using scalable machine learning to solve data-related problems is important
• A focus on using data science to create value is essential
• A strong interest in working across a variety of different industry sectors and problem areas.

BENEFITS

Up to £150,000 base salary
Competitive bonus
The opportunity to join a world-class and growing team

HOW TO APPLY

Please register your interest by sending your CV via the Apply link on this page. For further details or to enquire about other roles, please contact Nick Mandella at Harnham.

KEYWORDS

Python, SQL, AWS, GCP, Azure, Cloud, Databricks, Docker, Kubernetes, CI/CD, Terraform, Pyspark, Spark, Kafka, machine learning, statistics, Data Science, Data Scientist, Big Data, Artificial Intelligence, private equity, finance.

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Senior Data Scientist – Remote

We are working with a publishing company who have expanded into digital platforms and subscription-based businesses. They are focused on building personalised media experiences and improving user engagement across their platforms.

They are now hiring their first Data Scientist to join a team of analysts and engineers. This is a greenfield role, ideal for someone looking to make a tangible impact across a diverse set of brands, audiences, and digital products. Over time, this position will evolve into a leadership role.

What You’ll Be Doing

• Build, prototype and deploy models (with engineering support) across multiple brands.
• Drive user segmentation and clustering to improve personalisation and subscription performance.
• Collaborate with editorial and product teams to help predict content relevance using metadata tagging.
• Work on user experience optimisation, such as improving content recommendations and personalisation strategies across web, CRM and app platforms.
• Partner with the analytics and engineering teams to define data science best practices, tooling, and workflow.

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FULL STACK DATA SCIENTIST
PARIS (75)
45-60K€

Dans le cadre du développement de l’équipe Data Engineering, nous recrutons un(e) Data Engineer & Scientist Senior.

Le poste s’oriente davantage vers l’engineering, tout en conservant une dimension analytique au service des métiers (RH, marketing, satisfaction client).

VOTRE ROLE

Structurer, organiser et consolider la collecte de données existante

• Maintenir, modifier occasionnellement et faire évoluer des pipelines de données déjà en place
• Être autonome sur les sujets R&D Data, avec une forte composante scientifique (création de POC IA, analyse, modélisation, prédiction)
• Travailler en étroite collaboration avec les équipes métiers (RH, marketing, satisfaction client) pour transformer la donnée brute en insights métier
• Participer à la roadmap technique et scientifique sur 3, 6 et 12 mois, principalement autour des sujets IA et Data Engineering
• Manipuler les données via Python, SQL, PySpark, dans un environnement cloud (préférence AWS mais GCP/Azure possible)
• Construire et alimenter des dashboards avec des outils de data visualisation adaptés

VOTRE PROFIL

• 3 à 6 ans d’expérience en Data Engineering / Data Science
• Vous avez déjà travaillé dans un environnement startup ou scale-up, avec une forte autonomie et un esprit de construction
• Expérience en structuration d’un pôle data ou mise en place de pipelines from scratch appréciée
• Langages & outils : Python, Power BI ou Tableau (must have)
• Outils statistiques : SAS (must have), SPSS (nice to have)
• Cloud : AWS
• Français courant
• Diplômé(e) d’une école d’ingénieur ou grande école

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