Data Scientist, Lifecycle Marketing Job at Wealthfront (Palo Alto)

Data Scientist - Marketing

We're looking for a Data Scientist focused on marketing analytics to power the i...

Location

United Kingdom

Salary:

Not provided

ElevenLabs

Expiration Date

Until further notice

Requirements

Expertise in marketing and revenue analytics
Strong foundation in SQL and Python
Familiarity with analytics tools across the data stack
Experience working with CRM data (Salesforce preferred)
Understanding of B2B sales funnels, pipeline metrics, and lead lifecycle stages
Strong analytical intuition with an ability to connect marketing activities to business outcomes
A deep understanding of key marketing metrics such as CAC, conversion rates, pipeline velocity, and attribution
Experience building dashboards and reports that drive decision-making across marketing and sales teams
Proven ability to communicate findings clearly to non-technical stakeholders
Not afraid to get your hands dirty to get the job done

Job Responsibility

Power the insights that drive our B2B growth engine
Work at the intersection of data and go-to-market strategy
Help us understand what makes B2B prospects convert
Analyze which channels and campaigns drive the highest-quality pipeline
Advise on how to prioritize our marketing investments
Partner closely with marketing, sales, and revenue operations
Build dashboards that track funnel health
Develop lead scoring models that surface the right opportunities
Conduct deep-dive analyses that uncover what's working and what's not
Shape how we acquire and convert our most valuable customers through attribution modeling, campaign performance analysis, and understanding the B2B buyer journey

What we offer

Innovative culture
Growth paths
Learning & development supported through an annual discretionary stipend
Social travel with an annual discretionary stipend to meet up with colleagues
Annual company offsite
Co-working monthly stipend if not located near a main hub

Fulltime

Senior Data Scientist

At myPOS, we’re all about helping businesses grow and get paid. We make payments...

Location

Bulgaria , Sofia

Salary:

Not provided

myPOS

Expiration Date

Until further notice

Requirements

MSc or PhD in Computer Science, Statistics, Applied Mathematics, Econometrics or a related quantitative field (or equivalent commercial experience)
7+ years of applied data science and ML experience in a commercial environment, with a strong portfolio of models in production that drove measurable business outcomes
Expert Python for data science and ML engineering: pandas, scikit-learn, XGBoost / LightGBM, PyTorch or TensorFlow
clean, tested, modular code as a default
Deep expertise across the ML methodological spectrum: survival analysis, time-series and sequence modelling, uplift and causal inference, anomaly detection, and recommendation systems
Proven end-to-end ownership of at least three of: CLTV models, churn models, propensity models, fraud/risk models, recommendation or NBA systems - in a production commercial setting
Strong MLOps capability: feature stores, model registries, model serving infrastructure, drift monitoring, and CI/CD for ML pipelines
Deep SQL and data platform proficiency (GCP / BigQuery strongly preferred)
experience with streaming architectures for real-time feature generation
Hands-on expertise building LLM-powered applications: RAG pipelines, tool-use agents, multi-agent orchestration, and agent evaluation frameworks

Job Responsibility

Own the full lifecycle of complex modelling programmes across Customer & Commercial Intelligence: CLTV, Churn Prediction, Propensity to Buy, and Next Most Likely Product (NMLP)
Architect multi-horizon churn models and build the churn intervention scoring layer that prioritises at-risk merchants for Account Management teams
Lead the NMLP engine — designing and productionizing a multi-output recommendation system that identifies the next product across myPOS's full catalogue
Take technical ownership of core fraud model components: transaction-level classifiers, merchant behaviour anomaly detectors, and new-account fraud scorers optimised for high-throughput, low-latency inference
Architect and own the Next Best Action (NBA) decisioning engine - a real-time system that selects the highest-expected-value action for each merchant at every interaction
Design and build production-grade agentic AI systems that automate high-value analytical and operational workflows
Define and execute experiment designs for online evaluation - A/B tests, uplift experiments, and bandits - and analyse results with statistical rigour
Set and enforce technical standards across the team: code quality, reproducibility, evaluation rigour, model documentation, and MLOps practices
Produce high-quality model documentation and present complex modelling work clearly to stakeholders across Sales, Marketing, Risk, Product, and Operations

What we offer

Excellent compensation package
25 days annual paid leave (+1 day per year up to 30)
Full "Luxury" package health insurance including dental care and optical glasses
Meal vouchers of 102.26 EUR per month
Fully covered Multisport card
Fully covered public transport pass for Sofia
Free coffee, snacks and drinks at the office
Annual salary reviews, promotions and performance bonuses
myPOS Academy for upskilling and training
Unlimited access to courses on LinkedIn Learning

Fulltime

Data Scientist

My client is a modern, technology-led investment management firm leveraging adva...

Location

United States , Houston

Salary:

130000.00 USD / Year

Hunter Bond

Expiration Date

Until further notice

Requirements

1-4 years of hands-on experience in data analysis, EDA, and machine learning
Solid understanding of ML and statistical techniques (regression, classification, clustering, time series, model evaluation)
Strong Python skills and experience working with real-world datasets
Exposure to (or an interest in) finance/financial data is a strong plus
Degree in Data Science, Computer Science, Engineering, Mathematics, or similar

Job Responsibility

Performing exploratory analysis through to production-ready models
Shaping how data is used across the firm with direct visibility and ownership
Collaborating with engineers and quantitative analysts at the intersection of finance and tech
Working with live market data and decision-making systems that operate at scale
Contributing to the full lifecycle of data science projects

What we offer

Extremely competitive bonus tied to firm and individual performance
Direct exposure to investment and trading decision-making
Modern tech stack with real production ownership
Structured learning budget for courses, conferences, and certifications
Clear progression path into senior data science or quantitative roles
High-impact work- your models won’t sit on a shelf

Fulltime

Senior Data Scientist

As a (Senior) Data Scientist, you will play a key role in advancing core areas o...

Location

Germany , Düsseldorf

Salary:

Not provided

StepStone

Expiration Date

Until further notice

Requirements

Master's degree in Data Science, Mathematics, Computer Science or a related field
5+ years of experience in data science, business analytics, or AI integration, with at least 2 years in a role requiring strong communication and stakeholder management
hands-on experience with LLM fine-tuning and modern NLP frameworks
Proficiency in Python, SQL and familiarity with AWS SageMaker, Docker, and Airflow
Experienced in ML Engineering solutions (ML Ops tools), integrating models into enterprise systems
Strong ability to translate technical concepts into business language, to manage change and to drive adoption of AI solutions, balancing technical constraints with business priorities
Commitment to ethical and fair AI practices that ensure equitable outcomes for all users
Ability to working with C-suite, product managers, engineers, and operational teams

Job Responsibility

Partner with Marketing: Act as a strategic partner to the Marketing organisation and advocate for data-driven decision-making by effectively communicating AI strategy and its alignment with business objectives
Ensure stakeholders understand the value of AI-driven insights and leverage this knowledge to prioritize initiatives strategically
Lead the development lifecycle of machine learning and AI solutions in Marketing, from problem formulation and data exploration to model development, evaluation, and deployment
Keep abreast of advancements in AI/ML technologies and apply cutting-edge techniques where appropriate
Be an active member of our community: Collaborate with Data Science teams across the org to design intuitive interfaces and workflows for AI-driven recommendations and automation
Contribute to hackathons, training, and peer-to-peer knowledge exchange within the global data science community

What we offer

30 days of holidays + 2 extra days for Christmas and New Year's Eve
Hybrid working model
Company pension scheme
24/7 Employee Assistance Programme
Life Assurance Cover
Volunteering days
Job bike
Discounted parking or job ticket
In-house gym
In-house barista

Fulltime

Senior Data Scientist

As a Senior Data Scientist at myPOS, you will be the technical cornerstone of a ...

Location

Poland , Warsaw

Salary:

Not provided

myPOS

Expiration Date

Until further notice

Requirements

MSc or PhD in Computer Science, Statistics, Applied Mathematics, Econometrics or a related quantitative field (or equivalent commercial experience)
7+ years of applied data science and ML experience in a commercial environment, with a strong portfolio of models in production that drove measurable business outcomes
Expert Python for data science and ML engineering: pandas, scikit-learn, XGBoost / LightGBM, PyTorch or TensorFlow
clean, tested, modular code as a default
Deep expertise across the ML methodological spectrum: survival analysis, time-series and sequence modelling, uplift and causal inference, anomaly detection, and recommendation systems
Proven end-to-end ownership of at least three of: CLTV models, churn models, propensity models, fraud/risk models, recommendation or NBA systems - in a production commercial setting
Strong MLOps capability: feature stores, model registries, model serving infrastructure, drift monitoring, and CI/CD for ML pipelines
Deep SQL and data platform proficiency (GCP / BigQuery strongly preferred)
experience with streaming architectures for real-time feature generation
Hands-on expertise building LLM-powered applications: RAG pipelines, tool-use agents, multi-agent orchestration, and agent evaluation frameworks

Job Responsibility

Own the full lifecycle of complex modelling programmes across Customer & Commercial Intelligence: CLTV, Churn Prediction, Propensity to Buy, and Next Most Likely Product (NMLP)
Architect multi-horizon churn models and build the churn intervention scoring layer that prioritises at-risk merchants for Account Management teams
Lead the NMLP engine - designing and productionizing a multi-output recommendation system that identifies the next product across myPOS's full catalogue
Take technical ownership of core fraud model components: transaction-level classifiers, merchant behaviour anomaly detectors, and new-account fraud scorers optimised for high-throughput, low-latency inference
Architect and own the Next Best Action (NBA) decisioning engine - a real-time system that selects the highest-expected-value action for each merchant at every interaction
Design and build production-grade agentic AI systems that automate high-value analytical and operational workflows
Define and execute experiment designs for online evaluation - A/B tests, uplift experiments, and bandits - and analyse results with statistical rigour
Set and enforce technical standards across the team: code quality, reproducibility, evaluation rigour, model documentation, and MLOps practices
Produce high-quality model documentation and present complex modelling work clearly to stakeholders across Sales, Marketing, Risk, Product, and Operations

What we offer

Vibrant international team operating in hi-tech environment
Excellent compensation package
myPOS Academy for upskilling and training
Unlimited access to courses on LinkedIn Learning
Refer a friend bonus as we know that working with friends is fun
Teambuilding, social activities and networks on a multi-national level

Fulltime

Senior Data Scientist - Credit

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , New York

Salary:

Not provided

Plaid

Expiration Date

Until further notice

Requirements

5–10 years of experience in data science within the financial services industry
Deep familiarity with SQL and python
Deep understanding of credit risk and the development of underwriting models
Hands on credit expertise building and maintaining actual credit policies for lenders
Knowledge of lending lifecycle and how to optimize each step (marketing, acquisitions, customer management, collections/recoveries)
Demonstrated ability to make data driven decisions

Job Responsibility

Own the process for creating hands on recommendations for incorporating cash flow insights into lending decision using best practice for account level decisioning
Improve customer usage of Plaid insights data through custom analysis adoption specific customer need
Act as a subject matter expert for our credit insights credit policy implementation supporting data science, engineering, Go-to-Market
Applying your expertise in quantitative analysis, data mining, and data visualization to build models and insights
Identifying useful signals that can be fed into machine learning models
Informing and influencing product and engineering teams through your data analysis and presentations

Fulltime

Senior Data Scientist

As a Senior Data Scientist at myPOS, you will be the technical cornerstone of a ...

Location

Bulgaria , Sofia; Varna

Salary:

Not provided

myPOS

Expiration Date

Until further notice

Requirements

MSc or PhD in Computer Science, Statistics, Applied Mathematics, Econometrics or a related quantitative field (or equivalent commercial experience)
7+ years of applied data science and ML experience in a commercial environment, with a strong portfolio of models in production that drove measurable business outcomes
Expert Python for data science and ML engineering: pandas, scikit-learn, XGBoost / LightGBM, PyTorch or TensorFlow
clean, tested, modular code as a default
Deep expertise across the ML methodological spectrum: survival analysis, time-series and sequence modelling, uplift and causal inference, anomaly detection, and recommendation systems
Proven end-to-end ownership of at least three of: CLTV models, churn models, propensity models, fraud/risk models, recommendation or NBA systems - in a production commercial setting
Strong MLOps capability: feature stores, model registries, model serving infrastructure, drift monitoring, and CI/CD for ML pipelines
Deep SQL and data platform proficiency (GCP / BigQuery strongly preferred)
experience with streaming architectures for real-time feature generation
Hands-on expertise building LLM-powered applications: RAG pipelines, tool-use agents, multi-agent orchestration, and agent evaluation frameworks

Job Responsibility

Own the full lifecycle of complex modelling programmes across Customer & Commercial Intelligence: CLTV, Churn Prediction, Propensity to Buy, and Next Most Likely Product (NMLP)
Architect multi-horizon churn models and build the churn intervention scoring layer that prioritises at-risk merchants for Account Management teams
Lead the NMLP engine - designing and productionizing a multi-output recommendation system that identifies the next product across myPOS's full catalogue
Take technical ownership of core fraud model components: transaction-level classifiers, merchant behaviour anomaly detectors, and new-account fraud scorers optimised for high-throughput, low-latency inference
Architect and own the Next Best Action (NBA) decisioning engine - a real-time system that selects the highest-expected-value action for each merchant at every interaction
Design and build production-grade agentic AI systems that automate high-value analytical and operational workflows
Define and execute experiment designs for online evaluation - A/B tests, uplift experiments, and bandits - and analyse results with statistical rigour
Set and enforce technical standards across the team: code quality, reproducibility, evaluation rigour, model documentation, and MLOps practices
Produce high-quality model documentation and present complex modelling work clearly to stakeholders across Sales, Marketing, Risk, Product, and Operations

What we offer

Excellent compensation package
25 days annual paid leave (+1 day per year up to 30)
Full Luxury package health insurance including dental care and optical glasses
Meal vouchers of 102.26 EUR per month
Fully covered Multisport card
Fully covered public transport pass for Sofia
Free coffee, snacks and drinks at the office
Annual salary reviews, promotions and performance bonuses
myPOS Academy for upskilling and training
Unlimited access to courses on LinkedIn Learning

Fulltime

Data Scientist

We are seeking a Data Scientist to design and develop analytical models and insi...

Location

India , Pune

Salary:

Not provided

Vodafone

Expiration Date

Until further notice

Requirements

Experienced in advanced analytics techniques, including descriptive and predictive modelling
Comfortable working with complex, high‑volume, high‑dimensional datasets, preferably using Hadoop or Spark
Proficient in SQL and experienced with databases such as Teradata, Oracle, or MySQL
Strong knowledge of machine learning techniques and their application in real‑world scenarios
Hands‑on experience with statistical and analytical tools such as Python, R, SAS, MATLAB, or SPSS
Educated to degree level in Data Science, Applied Mathematics, Statistics, Computer Science, Engineering, or a related field, with 3–5+ years of relevant experience
Experienced in working within international and distributed teams
Demonstrates strong analytical, troubleshooting, and system analysis skills
Communicates complex ideas clearly in plain language, both verbally and in writing, with full professional fluency in English
Brings a flexible, proactive, and improvement‑focused mindset, with the ability to innovate and work within agile development environments

Job Responsibility

Design, build, test, and deliver analytical models using new and existing datasets to support defined business use cases
Perform data preparation, cleansing, and optimisation across SQL and No‑SQL data stores
Develop descriptive, predictive, and other analytical models for specific segments such as markets, products, or services
Contribute effectively to business decision‑making by translating analytical outcomes into clear, actionable recommendations
Work closely with commercial and business teams to present insights and recommended actions derived from models
Support product management by identifying and defining customer‑facing analytics use cases for the product roadmap
Contribute to defining and improving analytics lifecycle processes to enable fast and cost‑effective development
Participate in business analysis activities and document specifications for business information requests

What we offer

Exposure to complex, real‑world analytics challenges across multiple international markets
Opportunities to influence business decisions through data‑driven insights
Collaboration with diverse, cross‑functional, and global teams
A role that supports continuous learning, innovation, and process improvement within analytics and data science

Fulltime

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Data Scientist, Lifecycle Marketing

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