iCapital
financial services and alternative investments
DataAnalytics-Associate
Neural analysis suggests this role is
optimal for Mid candidates.
“Data Analytics - Associate at iCapital. Skills: Python, SQL, dbt, statistics, ML models, Tableau. Write Python and SQL (in dbt) to extract, transform, validate, and aggregate data. Conduct exploratory data analyses”
What You'll Achieve.
measurably drive growth for the business teams using analytics, data science and machine learning; define, calculate and grow their key operating metrics (i. e. sales conversion, marketing conversion, product adoption, CAC/CLTV)
Industry & Context.
understand complex business problems; exploratory data analyses; statistical inference
What They're Looking For.
Must Have
Bachelor’s degree or higher in computer science, economics, mathematics, statistics or a related technical field, 5-8 years of experience in an data-related role, Excellent knowledge of SQL, Excellent knowledge of Python, Excellent knowledge of pandas, Very good knowledge of statistics, Very good knowledge of ML models, Very good knowledge of ML services and infra, Knowledge of data modeling, Knowledge of relational databases, Knowledge of normalization, Knowledge of OLAP stores writing, writing skills, communication skills, presentation skills
Nice to Have
dbt experienced is preferred, Experience in the financial services and alternative investments space, Experience with product or marketing analytics (i. e. adoption or retention analyses, customer journey, user segmentation, CLTV and CAC calculations, conversion funnels)
What You'll Do.
Write Python and SQL (in dbt) to extract
Conduct exploratory data analyses
build machine learning models
develop ML infra in Jupyter and Python
Develop statistical models
construct data-driven experiments (e.g. A tests)
Visualize key metrics using Tableau
Build data sets using dbt and SQL
visualize measures of success using Tableau
formulate exploratory data analyses using pandas and Jupyter
develop statistical and machine learning models using Python
deploy production-ready code using GitLab
Gather requirements from internal stakeholders
conduct exploratory data analyses
perform statistical inference
deploy machine learning models to production
How You'll Work.
Team & Collaboration
work with our Sales, Marketing and Product groups; sit in the Analytics group of the broader Chief Data Office (CDO) team; work closely with the Business Intelligence, Data Engineering and Machine Learning teams; interface with internal stakeholders; Work closely with our engineering, product and business teams; Gather requirements from internal stakeholders
Communication Scope
communication skills; presentation skills
Process & Methodology
develop execution plans
Full Job Description
About the Role iCapital is looking to hire an Analytics Engineer Associate to measurably drive growth for the business teams using analytics, data science and machine learning. This role will work with our Sales, Marketing and Product groups to define, calculate and grow their key operating metrics (i. e. sales conversion, marketing conversion, product adoption, CAC/CLTV). This individual will sit in the Analytics group of the broader Chief Data Office (CDO) team and work closely with the Business Intelligence, Data Engineering and Machine Learning teams. This is a technical, individual contributor role that blends data engineering, data analytics, data science and machine learning. The ideal candidate will be able to understand complex business problems, interface with internal stakeholders, develop execution plans, implement all aspects of the project technically, and finally present on their work. Responsibilities Write Python and SQL (in dbt) to extract, transform, validate, and aggregate data. Conduct exploratory data analyses, build machine learning models and develop ML infra in Jupyter and Python. Develop statistical models and construct data-driven experiments (e. g. A/B tests). Visualize key metrics using Tableau. Work closely with our engineering, product and business teams to form a thorough understanding of our industry and evolving data model. Build data sets using dbt and SQL, visualize measures of success using Tableau, formulate exploratory data analyses using pandas and Jupyter, develop statistical and machine learning models using Python, and finally deploy production-ready code using GitLab. Gather requirements from internal stakeholders, conduct exploratory data analyses, perform statistical inference, and deploy machine learning models to production. Qualifications Bachelor’s degree or higher in computer science, economics, mathematics, statistics or a related technical field 5-8 years of experience in an data-related role Excellent knowledge o
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