Data Scientist

Centerfield•Los Angeles, CA

10d•$95,000 - $115,000•Hybrid

About The Position

Centerfield is seeking a Data Scientist with at least 2 years of experience to transform complex data into models, insights, and recommendations that improve business performance. The role addresses customer behavior, marketing effectiveness, sales conversion, and forecasting, in partnership with business stakeholders, data engineers, and machine learning engineers. It combines statistical and machine learning fundamentals with applying AI and large language models to practical business problems. This is a hybrid position requiring work from Centerfield’s Playa Vista, California office every Tuesday, Wednesday, and Thursday. The role is not restricted to the listed responsibilities, and its scope may change.

Requirements

At least 2 years of experience in data science or a closely related role applying statistical analysis and machine learning to business problems.
Strong SQL skills and proficiency in Python for data preparation, analysis, modeling, and evaluation.
Solid foundation in statistics and machine learning, including regression, classification, clustering, and hypothesis testing.
Experience with feature engineering, model validation, and selecting appropriate evaluation metrics, including understanding overfitting and data leakage.
Ability to work with AI and large language models, demonstrated through professional, academic, or personal projects; familiarity with prompting, working with model outputs, and evaluating accuracy and reliability.
Ability to translate ambiguous business questions into a structured analytical approach and actionable recommendations.
Attention to data quality, reproducibility, and documentation, with familiarity using version control.
Strong communication skills and ability to collaborate across technical and business teams.

Nice To Haves

Experience with GCP, BigQuery, or comparable cloud data platforms.
Experience in digital marketing, customer acquisition, sales, or customer analytics.
Experience with forecasting, propensity modeling, customer lifetime value, or experiment design.
Familiarity with LLM APIs, embeddings, retrieval-augmented generation (RAG), or evaluating AI-powered applications.
Experience partnering with engineering teams to deploy and monitor models.

Responsibilities

Partner with marketing, sales, and operations teams to define business problems, establish success metrics, and identify opportunities to improve conversion, revenue, and efficiency.
Explore and combine data from multiple sources using SQL and Python; investigate data quality issues, develop features, and document assumptions.
Build and evaluate predictive models for use cases such as customer propensity, lifetime value, segmentation, and forecasting.
Apply statistical analysis and experimentation to understand performance drivers, measure impact, and communicate uncertainty and limitations.
Develop reusable analytical workflows and automate recurring analyses to support faster, more consistent decision-making.
Collaborate with engineering teams to integrate models into business workflows and monitor their performance over time.
Apply AI and large language models to use cases such as extracting insights from unstructured data and supporting analytical workflows; evaluate output quality, reliability, cost, and appropriate data handling.
Present findings to technical and nontechnical audiences, explain trade-offs, and recommend clear next steps.

Benefits

Competitive salary and semi-annual bonus.
Unlimited PTO.
Medical, dental, and vision plans.
Generous parental leave.
401(k) company match plan, fully vested on day 1.
Outside patio with cabanas, firepits, and working grills.
Monthly happy hours, catered lunches, and daily food trucks.
Fully stocked kitchens with snacks and drinks.
Breakroom with games, couches, workout equipment, and weekly in-office exercise classes.
Free onsite gym and locker rooms.
Paid charity and volunteer days.
Monthly team outings.
Career growth and promotion opportunities.