Data Scientist ML Pipelines, GenAI *** Direct End Client ***

Overview

On Site
Depends on Experience
Accepts corp to corp applications
Contract - W2
Contract - Independent
Contract - 12 Month(s)

Skills

Analytics
Artificial Intelligence
Big Data
Cloud Computing
Data Analysis
Data Science
Deep Learning
Generative Artificial Intelligence (AI)
Statistical Models
Statistics
SQL
R
Python
Marketing
Machine Learning (ML)
Time Series
Senior Data Scientist
machine learning
AI
generative AI
recommender systems
data science models
personalization
targeting
monetization
feature engineering
user engagement
business metrics
time series analysis
collaborative filtering
matrix factorization
experiment design
statistical modeling
personal finance
cloud technologies
business impact
monetization strategy
user experience
data-driven decisions
machine learning models.
GenAI
Data Scientist
ML Pipelines

Job Details

Job Title: Senior Data Scientist

We are seeking a Senior Data Scientist to join our dynamic team and help solve real-world financial challenges using machine learning and data science techniques. In this role, you will be responsible for applying cutting-edge AI and statistical methods to deliver data-driven insights and actionable recommendations that drive business decisions. You will play a pivotal role in shaping financial products and user experiences, helping millions of users achieve their financial goals.

This highly cross-functional position will collaborate closely with engineering, product, marketing, finance, and analytics teams to implement machine learning models and data science strategies that improve engagement, monetization, and personalization. You will also drive innovation in emerging technologies like Generative AI, Deep Learning, and Recommender Systems to enhance personal finance solutions.

Key Responsibilities:

  • Collaborate Across Teams: Work closely with engineering, product, marketing, and other teams to identify opportunities to leverage data and improve financial products.

  • Drive Business Impact: Accelerate revenue and engagement through improvements in data science models, including marketing campaigns, targeting, personalization, and feature engineering.

  • Machine Learning Model Development: Apply statistical and machine learning techniques to build and optimize models that solve real-world financial problems.

  • Research & Innovation: Participate in research efforts exploring Generative AI, Deep Learning, and Recommender Systems for personal finance applications.

  • Metrics Definition & Experimentation: Collaborate with teams to define key business metrics and design experiments that measure revenue, user engagement, and experience.

  • Cross-functional Leadership: Represent the data science team in meetings and reviews, translating complex technical concepts to business stakeholders.

  • External Representation: Act as an ambassador for the data science team by representing the company at conferences, meetups, and external forums.

What s Great About the Role:

  • Work with large-scale machine learning models to optimize personal finance products.

  • Be part of a high-impact team driving significant improvements to business and user experiences.

  • Experience personal and professional growth while contributing to a culture of continuous improvement.

  • Play a key role in the development of AI-powered financial solutions and help millions of members achieve their financial goals.

Minimum Qualifications:

  • Education: MS in Computer Science, Mathematics, Statistics, Physics, or a related quantitative discipline.

  • Experience: 5+ years in Data Science, Machine Learning, and related areas, ideally in fast-paced, consumer-focused environments.

  • Technical Expertise:

    • Strong knowledge of Python and R for statistical analysis and model development.

    • Expertise in SQL for working with large datasets.

    • Familiarity with advanced modeling techniques such as deep neural networks, collaborative filtering, matrix factorization, time series analysis, and mixed-effects models.

  • Statistical Acumen: Strong statistical understanding of data at scale and experience with designing and conducting experiments.

Preferred Qualifications:

  • Experience driving monetization, member engagement, and long-term user value through AI solutions.

  • Experience in large-scale AI systems, generative AI, and self-serve analytics within the data science field.

  • Ability to thrive in a fast-paced environment at a large-scale company.

  • Experience in the ads business and product management.

Senior Data Scientist, machine learning, AI, deep learning, generative AI, recommender systems, Python, R, SQL, data science models, personalization, targeting, monetization, feature engineering, user engagement, business metrics, data analysis, time series analysis, collaborative filtering, matrix factorization, experiment design, big data, statistical modeling, personal finance, cloud technologies, business impact, monetization strategy, user experience, data-driven decisions, artificial intelligence, machine learning models.

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