Data Scientist

Blackline Systems Inc; United States; Hybrid; USD 149,000 - 187,000; Full time

Job summary

BlackLine is seeking a Data Scientist to join its Product & Technology organization to transform data into actionable insights and AI-driven solutions. You will explore large-scale datasets, shape intelligent features, and empower next‑gen AI capabilities in a performance‑driven, product‑oriented environment.

You’ll collaborate with product and engineering leaders on data pipelines, model integration, and experimentation.

Qualifications

• Experience deriving insights from large-scale data in SaaS/FinTech.
• Strong ML fundamentals and interpretable models.
• Experience with data pipelines and model deployment.

Responsibilities

• Analyze historical datasets to inform product strategy.
• Collaborate with engineering on data pipelines and model integration.
• Evaluate LLM-based and agentic workflows for performance.

Skills

Advanced analytics

Machine learning

Feature engineering

Large Language Models

Data storytelling

Statistical modeling

SQL

NoSQL

Graph databases

Cloud platforms

Communication

Problem solving

Education

MS/PhD in Math/CS/Stats

Tools

Snowflake

BigQuery

Vertex AI

AWS ML stack

Job description

Make Your Mark

We are looking for a Data Scientist to join our Product & Technology organization and play a pivotal role in transforming data into actionable intelligence and forward-looking innovation. This role sits at the intersection of advanced analytics, machine learning, and emerging AI paradigms (LLMs and agentic systems). You will work closely with product and engineering leadership to unlock insights from complex, large-scale datasets, shape intelligent features, and enable the next generation of AI-powered solutions. This is an ideal role for a curious, self-driven problem solver who thrives on exploring data deeply, asking the right questions, and translating findings into meaningful business impact.

You’ll Get To

Advanced Data Analysis & Insight Generation

• Collaborate with Product & Technology leadership to analyze historical datasets, extracting insights across:
• Longitudinal trends
• Behavioral and transactional patterns
• Translate complex data into clear, actionable insights that inform product strategy and decision‑making
• Answer targeted business questions related to customers, industry dynamics, and operational performance
• Machine Learning & Feature Engineering
• Guide ML teams in designing and refining feature engineering strategies
• Apply strong ML fundamentals to ensure robust, scalable, and interpretable models
• Partner with engineering teams to ensure effective data pipelines and model integration
• AI & Agentic Systems Enablement
• Collaborate with Agentic AI teams to design optimal context vectors and data representations for LLM-driven systems
• Contribute to the development and evaluation of LLM-based and agentic workflows
• Ensure data quality and structure support high-performance AI reasoning and retrieval
• Innovation & Experimentation
• Conduct data‑driven, empirical analysis of new business ideas, assessing feasibility, relevance, and potential impact
• Build prototypes, experiments, and analytical models to validate hypotheses quickly and rigorously
• Continuously explore new techniques across AI, ML, and data science to drive innovation

What You’ll Bring

• Master's or Ph.D. in Mathematics, Computer Science, Statistics, or a closely related field
• 5+ years of experience as a Data Scientist or Machine Learning Engineer
• Proven track record of deriving meaningful insights from large-scale historical data
• Experience working in data-intensive, product-driven environments, preferably in SaaS or FinTech
• Strong foundation in machine learning fundamentals and practical model development
• Deep experience in feature engineering and data preparation techniques
• Proficiency across data persistence paradigms:
  • SQL (relational databases)
  • NoSQL systems
  • Graph databases
• Experience with modern data platforms:
  • Preferred: Snowflake and/or Google Cloud (BigQuery, Vertex AI, etc.)
  • Alternative: AWS-native data and ML stack
• Working experience with Large Language Models (LLMs) and agentic AI systems
• Understanding of context construction, embeddings, and retrieval strategies
• Core Attributes
• Highly innovative, curious, and self-motivated
• Strong analytical and problem-solving mindset
• Customer-focused, with the ability to align data insights to real-world business needs
• Effective communicator, capable of translating technical findings into clear business narratives

Salary Range: $149,000.00-$187,000.00

Pay Transparency Statement: Placement within this range depends upon several factors, including the applicant's prior relevant job experience, skill set, and geographic location.

In addition to base pay, BlackLine also offers short-term and long-term incentive programs, based on eligibility, along with a robust offering of benefit and wellness plans.

We are committed to pay transparency and ensuring candidates have clear information about compensation expectations. For roles that include variable incentive components such as an Incentive Compensation Plan (ICP) or On-Target Earnings (OTE), the compensation structure may follow a split model - for example, a 50/50, 70/30, or 60/40 ratio between base salary and variable incentive.

BlackLine is committed to creating an inclusive and accessible experience for all candidates.

BlackLine is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity or expression, race, ethnicity, age, religious creed, national origin, physical or mental disability, ancestry, color, marital status, sexual orientation, military or veteran status, status as a victim of domestic violence, sexual assault or stalking, medical condition, genetic information, or any other protected class or category recognized by applicable equal employment opportunity or other similar laws.

BlackLine recognizes that the ways we work and the workplace itself has shifted. We innovate in a workplace that optimizes a combination of virtual and in-person interactions to maximize collaboration and nurture our culture. Candidates who live within a reasonable commute to one of our offices will work in the office at least 3 days a week.