Applied Data Finance
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Applied Data Finance tech stack

Applied Data Finance builds mostly with Python, SQL, SAS. Its stack also includes AWS, Spark, Amazon Redshift, Apache Iceberg. Python is named in 9 of the 9 job postings Applied Data Finance published in the last 12 months (100%). Counted by Alion from the job postings of Applied Data Finance, updated Nov 13, 2026.

Source: Alion Coverage: the company's job postings of the last 12 months Nov 13, 2026
Technologies in use
42
Postings analysed
9
Open now
6
Modernity
72 /100
New in 6 months
8

What programming languages does Applied Data Finance use?

Python is named in 100% of job postings at Applied Data Finance, followed by SQL (100%), SAS (11%).

Python 9 100% required in 89% · 6 open now · since Jul 2026
SQL 9 100% required in 89% · 6 open now · since Jul 2026
SAS 1 11% required in 100% · 1 open now · since Oct 2026

What frameworks and libraries does Applied Data Finance use?

Boto3 is named in 22% of job postings at Applied Data Finance, followed by Dask (22%), Pandas (22%), Polars (22%).

Boto3 2 22% required in 100% · 2 open now · since Oct 2026
Dask 2 22% required in 100% · 2 open now · since Oct 2026
Pandas 2 22% required in 100% · 2 open now · since Oct 2026
Polars 2 22% required in 100% · 2 open now · since Oct 2026
SHAP 2 22% optional · since Sep 2026
XGBoost 1 11% required in 100% · 1 open now · since Oct 2026

What databases does Applied Data Finance use?

Amazon Redshift is named in 33% of job postings at Applied Data Finance, followed by Apache Iceberg (33%), Snowflake (11%).

Amazon Redshift 3 33% required in 100% · 3 open now · since Sep 2026
Apache Iceberg 3 33% required in 33% · 3 open now · since Sep 2026
Snowflake 1 11% required in 100% · 1 open now · since Sep 2026

What cloud and platforms does Applied Data Finance use?

AWS is named in 44% of job postings at Applied Data Finance, followed by Spark (44%), Tableau (33%), Amazon EC2 (22%).

AWS 4 44% required in 100% · 4 open now · since Sep 2026
Spark 4 44% required in 100% · 4 open now · since Sep 2026
Tableau 3 33% required in 67% · 3 open now · since Sep 2026
Amazon EC2 2 22% required in 100% · 2 open now · since Oct 2026
Bitbucket 2 22% required in 100% · 2 open now · since Oct 2026
Power BI 2 22% required in 100% · 2 open now · since Oct 2026
Airflow 2 22% optional · 2 open now · since Oct 2026
Amazon S3 1 11% required in 100% · 1 open now · since Sep 2026
Show all (12)
Databricks1
Alation1
Apache Kafka1
Collibra1

What developer tools does Applied Data Finance use?

Git is named in 33% of job postings at Applied Data Finance, followed by pySpark (33%), Copilot (22%), Pentaho (22%).

Git 3 33% required in 67% · 3 open now · since Sep 2026
pySpark 3 33% required in 67% · 3 open now · since Sep 2026
Copilot 2 22% required in 100% · 2 open now · since Oct 2026
Pentaho 2 22% required in 100% · 2 open now · since Oct 2026
dbt 2 22% optional · 2 open now · since Oct 2026
Jenkins 1 11% optional · 1 open now · since Sep 2026
Rest API 1 11% optional · 1 open now · since Sep 2026
Terraform 1 11% optional · 1 open now · since Sep 2026

Which engineering practices does Applied Data Finance ask for?

Machine Learning is named in 44% of job postings at Applied Data Finance, followed by Data Vault (33%), Dimensional Modeling (33%), ETL/ELT (33%).

Machine Learning 4 44% required in 100% · 3 open now · since Sep 2026
Data Vault 3 33% required in 67% · 3 open now · since Sep 2026
Dimensional Modeling 3 33% required in 67% · 3 open now · since Sep 2026
ETL/ELT 3 33% required in 67% · 3 open now · since Sep 2026
AI Agents 2 22% required in 100% · 2 open now · since Oct 2026
Agentic Workflows 2 22% required in 100% · 2 open now · since Oct 2026
Feature Store 2 22% required in 100% · since Sep 2026
A/B Testing 1 11% optional · since Jul 2026
Show all (10)
CI/CD1
Platform Engineering1

What does each Applied Data Finance team work with?

The technologies each team's postings require most often, with the number of postings that require them.

Data Science

4 postings
Python3
SQL3

Leadership

3 postings
Python3
SQL3

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How is the Applied Data Finance stack changing?

Read from the dates of the postings themselves: a technology is new when the first posting that names it appeared in the last six months, rising or falling when its share of postings moved between the last two quarters.

First appeared
AI AgentsOct 2026
Agentic WorkflowsOct 2026
Amazon EC2Oct 2026
BitbucketOct 2026
Boto3Oct 2026
CopilotOct 2026
DaskOct 2026
PandasOct 2026

How modern is the Applied Data Finance stack?

Modern 72/100

Applied Data Finance scores 72 out of 100 (Modern). The score averages how current each technology in the stack is and adds weight for AI adoption. AI technologies in the stack: 0; legacy ones: 0.

How common is the Applied Data Finance stack in its industry?

Share of the 550 companies in the same industries, whose stack Alion knows, that use each technology.

Python58%
SQL65%
AWS40%
Spark13%
Amazon Redshift7%
Apache Iceberg2%
Tableau18%
Airflow5%
Amazon EC27%
Bitbucket3%

What sets Applied Data Finance apart

Apache Iceberg2%

Questions about the Applied Data Finance tech stack

What programming languages does Applied Data Finance use?

The languages named in Applied Data Finance job postings are Python (100%), SQL (100%), SAS (11%), as a share of the 9 postings of the last 12 months.

Does Applied Data Finance use Boto3?

Yes. Boto3 is named in 2 of 9 job postings (22%) and required in 2 of them.

What cloud and platforms does Applied Data Finance use?

The cloud and platforms named in Applied Data Finance job postings are AWS (4), Spark (4), Tableau (3) (postings in brackets).

What skills do you need for a Data Science job at Applied Data Finance?

Data Science postings at Applied Data Finance most often require Python (3), SQL (3), out of 4 postings in the last 12 months.

Is the Applied Data Finance tech stack changing?

Yes. AI Agents, Agentic Workflows, Amazon EC2, Bitbucket first appeared in Applied Data Finance job postings in the last six months.

How modern is the Applied Data Finance tech stack?

Applied Data Finance scores 72 out of 100 (Modern). The score averages how current each technology in the stack is and adds weight for AI adoption. AI technologies in the stack: 0; legacy ones: 0.

How does Alion know the Applied Data Finance tech stack?

Alion reads every job posting Applied Data Finance publishes and tags the technologies each one names. The figures on this page count the 9 postings of the last 12 months and were updated on Nov 13, 2026.

Method and citation

Alion reads every job posting the company publishes and tags the technologies each one names. Shares count the postings of the last 12 months, open and closed; the company's own products are counted apart. How we count

Alion, "Applied Data Finance tech stack: 42 technologies from 9 job postings", as of Nov 13, 2026. https://alion.io/company/applied-data-finance/technologies

Licence: CC BY-SA 4.0JSON