Data Scientist

Overview

Hybrid
Depends on Experience
Full Time

Skills

Data scientist
Python
Statistics
Communication
dbt
Product Analytics
Marketing Analytics
Pandas
Tableau
SQL
Jupyter
Data analytics
Gitlab
ML
OLAP

Job Details

Data Scientist, Assistant Vice President

For our direct client, a leading fintech firm focused on alternative investments, we seek an experienced Data Scientist,  to measurably drive growth for the company's business teams using analytics, data science and machine learning.

This is an onsite role, at the company's office near Grand Central Terminal in New York City, with flexibility to work from home on Fridays.  

In this role, you will work with our Sales, Marketing and Product groups to define, calculate and grow their key operating metrics (e.g. sales conversion, marketing conversion, product adoption, CAC/CLTV). You will sit in the Analytics group of the broader Chief Data Office (CDO) team and work closely with our Business Intelligence, Data Engineering and Machine Learning teams.

Day-to-day, you will requirements gather from internal stakeholders, conduct exploratory data analyses, perform statistical inference, and deploy machine learning models to production. You will be our subject matter expert when it comes to data science and machine learning.

At a technical level, you will build data sets using dbt/SQL, visualize measures of success using Tableau, formulate exploratory data analyses using pandas/Jupyter, develop statistical and machine learning models using Python, and finally deploy production-ready code using GitLab.

This is a technical, individual contributor role that blends data engineering, data analytics, data science and machine learning. Ideal candidates 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

Required Qualifications:

· Bachelor’s degree or higher in Computer Science, Economics, Mathematics, Statistics or a related technical field

· 5 to 8 years of experience in an data-related role

· Excellent knowledge of SQL (dbt experienced preferred), Python and pandas

· Very good knowledge of statistics, ML models and ML services/infra

· Good knowledge of data modeling, relational databases, normalization, OLAP stores

· Good writing, communication and presentation skills

· Familiar with a business intelligence tool (e.g. Tableau, Looker, PowerBI)

Preferred Qualifications:

· Prior experience in the financial services and alternative investments

· Prior experience with Product or Marketing Analytics (e.g. adoption/retention analyses, customer journey, user segmentation, CLTV/CAC calculations, conversion funnels)

Salary & Benefits 

The base salary range for this role is $120,000 to $170,000, depending on experience, plus full benefits and bonus potential

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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