Applied & Data Scientist

Role Overview

We are seeking a

Senior Data Scientist

with strong expertise in applied data science and machine learning. The role involves designing, developing, and deploying advanced models, building dashboards, and collaborating cross-functionally to deliver data-driven solutions that solve real-world business challenges.

Key Responsibilities

Design, build, and deploy advanced

AI / Data Science solutions

with a focus on scalability and ethical AI.

Apply expertise in

machine learning frameworks

and advanced techniques (LLM fine-tuning, RAG implementations, evaluation methods).

Conduct

applied research

in areas such as fraud detection, risk modeling, and automation.

Perform

data analysis and profiling

on large datasets (SQL / KQL), ensuring high-quality insights.

Collaborate with data engineers to validate pipelines, transformations, and ensure data accuracy.

Create and maintain

Power BI dashboards

aligned with business use cases.

Translate business needs into technical requirements and document

business rules, logic, and lineage .

Support

data governance

initiatives, metadata management, and gap analysis of current vs. target data flows.

Partner with engineering, product, and program management teams in an Agile environment.

Required Qualifications

Education & Experience

(one of the following) :

8+ years with a

Bachelor’s degree

in Statistics, Mathematics, Physics, Econometrics, Computer Science, Engineering, or related field.

6+ years with a

Master’s degree

in the same fields.

2+ years with a

Ph.D.

in the same fields.

Proven expertise in

statistical modeling, feature engineering, model evaluation, and data pipeline design .

Strong command of

SQL / KQL

for querying and profiling large datasets.

Experience with

data mapping, source-to-target documentation, and profiling .

Familiarity with

modern data platforms

(Microsoft Azure, Data Factory, Data Lake, Microsoft Fabric preferred).

Strong communication skills with ability to engage both technical and non-technical stakeholders.

Preferred Qualifications

Research contributions :

publications, patents, peer-reviewed work .

Hands-on coding experience in

Python

(C# is a plus).

Experience with

Power BI

(or similar BI tools).

Knowledge of

fraud detection workflows, vendor data integration, and cost optimization .

Familiarity with

Agile or hybrid Agile / Waterfall delivery methods .

Proficiency with

Excel, Visio, or other documentation tools .