Data Annotator - Data Scientist

This

position

is

listed

on

behalf

of

a

partner

company,

who

manages

all

applications

and

next

steps.

Our

partner

is

looking

for

a

Data

Annotator

–

Data

Scientist

based

in

India

.

The

Data

Annotator

–

Data

Scientist

will

contribute

to

the

development

and

improvement

of

advanced

AI

systems

through

specialized

data

annotation,

technical

evaluation,

and

model

training

projects.

This

role

goes

beyond

traditional

data

annotation,

requiring

strong

expertise

in

data

science,

statistical

analysis,

and

machine

learning.

You

will

analyze

complex

datasets,

evaluate

analytical

methodologies,

and

assess

AI-generated

outputs

for

accuracy,

consistency,

and

technical

reliability.

Working

with

Python,

SQL,

and

modern

data

science

libraries,

you

will

help

improve

the

reasoning

and

analytical

capabilities

of

AI

models.

The

position

offers

an

opportunity

to

apply

practical

data

science

knowledge

to

real-world

AI

evaluation

challenges.

This

is

a

fully

remote,

flexible,

part-time

opportunity

for

professionals

passionate

about

data,

analytics,

and

artificial

intelligence.

Accountabilities

Data

Analysis

and

Interpretation:

Analyze

complex

datasets,

identify

meaningful

patterns,

evaluate

trends,

and

assess

the

accuracy

of

data-driven

conclusions.

Statistical

Analysis

and

Evaluation:

Review

statistical

methodologies,

probability

concepts,

hypothesis

testing,

regression

models,

and

statistical

interpretations.

Machine

Learning

Evaluation:

Assess

machine

learning

algorithms,

model

selection

strategies,

feature

engineering

techniques,

and

predictive

modeling

workflows.

Technical

Data

Annotation:

Produce

high-quality

annotations

for

data

science-related

datasets,

including

analytical

problems,

Python

code,

statistical

outputs,

and

technical

documentation.

AI-Generated

Output

Evaluation:

Evaluate

AI-generated

analytical

responses

for

mathematical

accuracy,

logical

consistency,

statistical

correctness,

and

contextual

relevance.

Python

Code

Assessment:

Review

Python-based

data

science

implementations,

identify

logical

errors,

evaluate

coding

approaches,

and

recommend

technically

sound

improvements.

SQL

and

Data

Query

Evaluation:

Analyze

SQL

queries,

data

extraction

processes,

joins,

aggregations,

and

query

accuracy.

Model

Performance

Assessment:

Evaluate

machine

learning

models

using

appropriate

performance

metrics,

validation

techniques,

and

statistical

measures.

Prompt

and

Response

Evaluation:

Review

prompts

and

AI-generated

responses

to

assess

technical

accuracy,

completeness,

relevance,

and

adherence

to

instructions.

Technical

Documentation:

Provide

clear

explanations,

structured

annotations,

technical

justifications,

and

actionable

feedback

for

evaluation

tasks.

Quality

Assurance:

Maintain

high

standards

of

annotation

accuracy

and

consistency

while

following

project-specific

guidelines

and

evaluation

requirements.

Requirements:

2–6

years

of

professional

experience,

with

at

least

2

years

in

Data

Science,

Applied

Science,

Data

Analytics,

Machine

Learning,

or

a

related

technical

field.

Strong

hands-on

programming

experience

with

Python.

Practical

experience

using

data

science

libraries

and

frameworks

such

as

Pandas,

NumPy,

and

Scikit-learn.

Solid

understanding

of

statistics,

probability,

hypothesis

testing,

and

mathematical

concepts.

Experience

with

machine

learning

algorithms,

predictive

modeling,

feature

engineering,

and

model

evaluation

techniques.

Proficiency

in

SQL

and

experience

querying,

manipulating,

and

analyzing

structured

datasets.

Familiarity

with

data

visualization

tools

such

as

Matplotlib,

Seaborn,

Tableau,

or

Power

BI.

Ability

to

independently

analyze

complex

datasets

and

assess

existing

analytical

models

and

implementations.

Familiarity

with

Jupyter

Notebooks

and

collaborative

data

science

development

workflows.

Strong

analytical

thinking,

problem-solving

abilities,

and

technical

reasoning

skills.

How Jobgether works

• We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
• We appreciate your interest and wish you the best!
• Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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