What you'll do:

• Build and own data pipelines that power the quantitative research system. Get data from

internal Design, develop and implement ML/AI solutions for real estate markets.

• Find the needle in the haystack - identify the signals that are most descriptive and predictive

of market performance.

• Train time series forecasting and cross-sectional ranking models across hundreds of

geographies and property types. Use these data-driven views to construct risk-efficient

model portfolios.

• Help the team build automated processes to support the quant research system using best

practices in data engineering, cloud computing, and software development.

• Communicate complex quantitative ideas & insights to investment teams (analysts, PMs,

underwriters, etc.) to improve adoption of solutions delivered by the data science team.

• Scope, lead, and execute research projects with clearly defined deliverables and timelines.

Provide input to leadership to support development of a long-term roadmap.

What makes you a great fit:

• Bachelor’s degree in computer science, engineering, or a quantitative discipline

• Minimum of 8 years of experience as a software engineer, data engineer, or ML engineer

• Expert-level knowledge in building and maintaining data pipelines and data warehouses

(especially Snowflake)

• Highly proficient in database design, data modeling, and basic admin tasks

• Proficient in SQL, python, and common data science libraries (e.g. pandas, numpy, scikit

learn)

Experience:

• Experience with financial data, building end-to-end systems (data, models, UI) driving

investment decisions

• Project management experience

• Proficient with cloud computing. Working with virtual machines, serverless functions, cloud

storage, data pipelines, etc. Azure is primary cloud, AWS/GCP also OK.

• Experience with Snowflake and ETL tools like Matillion & Azure Data Factory.

• Experience as a data analyst, data scientist, or BI developer. Able to switch roles based on

the team's current needs.

About Us:

At Coralogix, we’re rebuilding the path to observability using a real-time streaming analytics pipeline that provides monitoring, visualization, and alerting capabilities without the burden of indexing.

By enabling users to define different data pipelines per use case, we provide deep insights for less than half the cost.In short, we are streaming the future of data.