Data Scientist CV — page 1

Elena

Vasquez

Senior

Data

Scientist

elena

.

vasquez

@

email

.

com

+1 (415) 827-4613

San

Francisco

,

CA

linkedin

.

com

/

in

/

elenavasquez

·

github

.

com

/

evasquez

Data

scientist

with

6+

years

of

experience

building

production

ML

systems

in

high

-

growth

environments

.

Specialise

in

NLP

,

recommendation

systems

,

and

predictive

modelling

.

Passionate

about

translating

complex

data

into

actionable

business

outcomes

and

leading

cross

-

functional

teams

toward

measurable

impact

.

1 / 3

Data Scientist CV — page 2

SKILLS

Languages

&

Libraries

Python

R

SQL

PyTorch

TensorFlow

scikit

-

learn

XGBoost

Pandas

NumPy

Spark

MLOps

&

Infrastructure

Docker

Kubernetes

AWS

SageMaker

MLflow

Airflow

Git

CI

/

CD

Specialisations

NLP

Recommender

Systems

Time

Series

A

/

B

Testing

Bayesian

Statistics

Deep

Learning

EDUCATION

Stanford

University

M

.

S

.

in

Computer

Science

—

AI

Specialisation

2017 – 2019

UC

Berkeley

B

.

S

.

in

Statistics

&

Computer

Science

2013 – 2017

LANGUAGES

English

—

Native

Spanish

—

Native

Mandarin

—

Professional

working

proficiency

CERTIFICATIONS

AWS

Certified

Machine

Learning

–

Specialty

(2023)

Deep

Learning

Specialisation

deeplearning

.

ai

(2020)

TensorFlow

Developer

Certificate

(2021)

EXPERIENCE

Lumina

Health

—

Senior

Data

Scientist

Apr

2022 –

Present

Vercor

Analytics

—

Data

Scientist

Sep

2019 –

Mar

2022

BrightLine

Research

—

Junior

Data

Scientist

Jun

2018 –

Aug

2019

SELECTED

PROJECTS

Cross

-

Lingual

Document

Summariser

PyTorch

·

HuggingFace

·

FastAPI

Fine

-

tuned

a

multilingual

T

5

model

on

a

custom

corpus

of

50

k

English

–

Spanish

paired

documents

.

Deployed

as

a

REST

API

serving

10

k

+

requests

per

day

with

sub

-

second

latency

.

Market

Basket

Analysis

Engine

Spark

·

GraphX

·

PostgreSQL

Built

a

scalable

frequent

-

itemset

mining

system

processing

12

M

weekly

transactions

.

Generated

product

affinity

scores

used

by

the

merchandising

team

to

optimise

shelf

layouts

,

contributing

to

a

6%

lift

in

cross

-

category

sales

.

Designed

and

deployed

a

real

-

time

clinical

risk

prediction

pipeline

using

gradient

-

boosted

trees

,

reducing

ICU

readmission

rates

by

18%

across

12

hospital

partners

.

—

Led

development

of

a

transformer

-

based

NLP

system

for

extracting

structured

patient

histories

from

unstructured

clinical

notes

,

achieving

93%

accuracy

on

a

held

-

out

test

set

.

—

Built

a

Bayesian

A

/

B

testing

framework

that

enabled

product

teams

to

make

statistically

sound

rollout

decisions

,

accelerating

experiment

velocity

by

40%.

—

Mentored

a

team

of

4

data

scientists

and

established

code

review

practices

,

model

documentation

standards

,

and

reproducible

experiment

workflows

.

—

Built

a

multi

-

armed

bandit

recommendation

engine

for

a

SaaS

platform

serving

2.3

M

monthly

active

users

,

increasing

content

engagement

by

27%

and

session

duration

by

14%.

—

Developed

a

churn

prediction

model

using

XGBoost

and

engineered

features

from

behavioural

sequences

,

achieving

precision

of

0.82

at

recall

0.65

and

driving

a

22%

reduction

in

monthly

churn

.

—

Architected

an

automated

feature

engineering

pipeline

on

AWS

that

reduced

model

iteration

time

from

weeks

to

less

than

2

days

.

—

Partnered

with

product

managers

and

engineers

to

design

and

analyse

30+

controlled

experiments

,

influencing

the

product

roadmap

with

data

-

backed

recommendations

.

—

Developed

time

-

series

anomaly

detection

models

for

IoT

sensor

data

from

industrial

equipment

,

achieving

a

false

positive

rate

below

2%

on

production

streams

.

—

Implemented

a

real

-

time

dashboard

using

Python

,

Apache

Kafka

,

and

PostgreSQL

to

visualise

equipment

health

metrics

across

200+

monitored

assets

.

—

Conducted

statistical

analyses

to

validate

sensor

calibration

protocols

,

contributing

to

a

15%

reduction

in

maintenance

costs

.

—

2 / 3

Data Scientist CV — page 3

Drift

Detection

Monitor

(

Open

Source

)

Python

·

Evidently

·

MLflow

Created

an

open

-

source

library

for

real

-

time

drift

detection

in

production

ML

pipelines

using

statistical

distance

metrics

and

adaptive

thresholds

.

Currently

used

by

3

early

-

adopter

teams

in

production

.

3 / 3

Data Scientist CV

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