Current Employment Status:
Hired Part Time on Jan 18, 2025

Clairol

Data Analyst

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mark as hired

Overview

Looking for full-time work (8 hours/day)

at $11.61/hour ($2,240.00/month)

Bachelors degree

Last Active

June 18th, 2026 (20 days ago)

Member Since

May 26th, 2024

Profile Description

I have more than 6 years of experience in analyzing and interpreting data to support management's decision making. I worked as a data scientist for a multinational company. My responsibilities began at having a good understanding of the business and the data available. For every analytics initiative, I conducted exploratory data analysis and deep dive analysis on the business problem and presented them to stakeholders. The results of the analyses will provide insights to management/stakeholders if we are to proceed with the initiative. Upon management's approval, I created analytics solutions that varies from descriptive to prescriptive. As an example, for one initiative, I did the data cleaning and transformation to develop data marts / modules. Afterwards, from these data marts, I developed and trained predictive models. The output of the predictive models will be used on the campaigns that the business will be launching, focusing their effort on the segments/items that will provide value. For monitoring the effectiveness of the models and the campaigns, I developed a dashboard in Power BI. The dashboard must reflect the KPIs that the business wants to measure. Then, after every campaign, I conducted post-mortem analysis to provide the stakeholders a better understanding on what happened and the things that needed improvements.

Top Skills

Office and Administration » Microsoft Excel

Experience: 5 - 10 years

Software » Data Engineering » SQL

Experience: 5 - 10 years

I created the data marts / modules of the dashboard and predictive models I developed

Office and Administration » Power BI

Experience: 5 - 10 years

I created dashboards for campaign performance monitoring and model monitoring.

Other Skills

Office and Administration » Microsoft Power Point

Experience: 5 - 10 years

Software » Python

Experience: Less than 6 months

I used Python in doing exploratory data analysis and developing predictive models

Software » Data Engineering » R

Experience: 2 - 5 years

I created the curation layer developed forecasting models using R.

Software » Databases » Oracle

Experience: 2 - 5 years

Marketing » Marketing Analytics » Google Analytics

Experience: Less than 6 months

SEO » Ahrefs

Experience: Less than 6 months

Cloud Services » Azure » Analytics - Data Lake Storage

Experience: 2 - 5 years

Marketing » Marketing Analytics » Looker Studio

Experience: Less than 6 months

Office and Administration » Data Analytics » Tableau

Experience: 1 - 2 years

Basic Information

Age: 40

Gender: Female

Website: Sign Up with Pro Account to View

Address: An, Rizal

Tests Taken: IQ
Score: 129: DISC
Dominance: 45%
Influence: 20%
Steadiness: 30%
Compliance: 6%: English
C2(Advanced/Mastery)

Government ID: Sign Up with Pro Account to View

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BENCHMARKS

Loading Time: Base Classes	0.0008
Controller Execution Time ( Jobseekers / Info )	0.0575
Total Execution Time	0.0591

GET DATA

No GET data exists

MEMORY USAGE

1,631,488 bytes

POST DATA

No POST data exists

URI STRING

jobseekers/info/3459636

CLASS/METHOD

jobseekers/info

DATABASE: onlinejobs (Jobseekers:$db) QUERIES: 29 (0.0441 seconds) (Show)

0.0004	`SELECT * FROM exrates WHERE rate_name = 'USD-PHP'`
0.0010	SELECT * FROM `jobseekers` WHERE `jobseeker_id` = '3459636' LIMIT 1
0.0162	SELECT * FROM `jobseeker_meta` WHERE `jobseeker_id` = '3459636'
0.0124	SELECT `j`., `jj`. FROM `jobseekers` `j` INNER JOIN `jobseekers_jobdata` `jj` ON `j`.`jobseeker_id` = `jj`.`jobseeker_id` WHERE `j`.`jobseeker_id` = '3459636'
0.0006	SELECT * FROM `jobseekers_trust` WHERE `jobseeker_id` IS NULL
0.0005	SELECT * FROM `jobseekers` WHERE `jobseeker_id` = '3459636' AND `is_private` = 1
0.0003	`SELECT * FROM employment WHERE jobseeker_id = '3459636' AND hired > -1`
0.0004	`SELECT employers.contact_name, ec.employer_id, ec.jobseekers_id, ec.is_jobseeker_reply, ec.employer_date, ec.employer_comment, ec.lastmodified FROM employers LEFT JOIN employer_comment ec on employers.employer_id = ec.employer_id WHERE ec.jobseekers_id = '3459636' AND employers.deactivate = 0 ORDER BY employer_comment_id DESC`
0.0003	`SELECT * FROM skill_categories ORDER BY cat_order ASC`
0.0005	`SELECT * FROM skill_subcategories ORDER BY subcategory ASC`
0.0003	`SELECT * FROM jobseekers_jobdata WHERE jobseeker_id = 3459636 LIMIT 1`
0.0005	`SELECT * FROM jobseekers_skills WHERE jobseeker_id = 3459636 LIMIT 1`
0.0007	`SELECT * FROM jobseekers j, jobseekers_jobdata jj,jobseekers_skills js WHERE j.jobseeker_id = '3459636' AND j.jobseeker_id = jj.jobseeker_id AND jj.jobseeker_id = js.jobseeker_id`
0.0004	`SELECT *, DATEDIFF('2026-07-08',rebill_date) duration_rebill FROM employers WHERE employer_id = ''`
0.0003	`SELECT * FROM employer_comment WHERE employer_id = ''`
0.0013	SELECT `facebook`, `manual_fb_score` FROM `jobseekers_trust` WHERE `jobseeker_id` = '3459636'
0.0029	SELECT * FROM `skills_categories` WHERE `is_approved` = 1 ORDER BY `name`
0.0017	SELECT `jsct`., `jsct`.`id` as `jsct_id`, `sct`. FROM `jobseekers_skills_categories` `jsct` LEFT JOIN `skills_categories` `sct` ON `sct`.`id` = `jsct`.`skill_category_id` WHERE `sct`.`is_approved` = 1 AND `jsct`.`jobseeker_id` = '3459636' ORDER BY `jsct`.`rate` DESC
0.0005	SELECT * FROM `jobseekers_trust` WHERE `jobseeker_id` = '3459636'
0.0003	`SELECT user_level, rebill_date, jobseekers_seen, jobseekers_seen_override from employers WHERE employer_id = ''`
0.0004	SELECT * FROM `testimonial_videos` WHERE `placement` = 1 OR `placement` = 0 ORDER BY RAND()
0.0003	SELECT * FROM `testimonial_videos` WHERE `placement` = 2 OR `placement` = 0 ORDER BY RAND()
0.0002	`select * from teasers`
0.0004	SELECT * FROM `employers` WHERE `employer_id` IS NULL LIMIT 1
0.0002	`SELECT user_level, rebill_date, jobseekers_seen, jobseekers_seen_override from employers WHERE employer_id = ''`
0.0002	SELECT * FROM `employers` WHERE `employer_id` IS NULL LIMIT 1
0.0002	`SELECT user_level, rebill_date, jobseekers_seen, jobseekers_seen_override from employers WHERE employer_id = ''`
0.0002	`SELECT user_level, rebill_date, jobseekers_seen, jobseekers_seen_override from employers WHERE employer_id = ''`
0.0003	`SELECT * FROM notes WHERE employer_id = '0'`

HTTP HEADERS (Show)

SESSION DATA (Show)

__ci_last_regenerate	1783478698
last_page	https://v1.stage.onlinejobs.ph/jobseekers/info/3459636
csrf-token	115e2378ff29bdf7815a4851cfd4c127

CONFIG VARIABLES (Show)

base_url	https://v1.stage.onlinejobs.ph
log_threshold	2
enable_profiler
index_page
uri_protocol	PATH_INFO
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language	english
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composer_autoload	vendor/autoload.php
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enable_query_strings
controller_trigger	c
function_trigger	m
directory_trigger	d
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log_file_extension
log_file_permissions	420
log_date_format	Y-m-d H:i:s
error_views_path
cache_path
cache_query_string
encryption_key	OdBUArjiWg9I7u7bvAwQ7Fu35VB1kzga
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sess_expiration	2678400
sess_save_path
sess_match_ip
sess_time_to_update	300
sess_regenerate_destroy
cookie_prefix
cookie_domain
cookie_path	/
cookie_secure
cookie_httponly
standardize_newlines
global_xss_filtering	1
csrf_protection
csrf_token_name	csrf_test_name
csrf_cookie_name	csrf_cookie_name
csrf_expire	7200
csrf_regenerate	1
csrf_exclude_uris	Array ( )
compress_output
time_reference	local
rewrite_short_tags
proxy_ips
ojadmin	JpjZkQN5A8l@^L
salt	+UFjSAT49tPZLtmU2CIG2FYN7pRhgsWyLHgSyQa6k3I=
queue_enabled
twilio	Array ( [sid] => AC00c0594045c6eef9407e8fff01f3d467 [token] => f0bfc0b73444a077894a43f5f75e6d41 [length] => 6 [from] => +639221200200 [code_expiry_seconds] => 14400 )
maintenance	Array ( [admin] => Array ( [verification] => ) [announcement_bar] => Array ( [show_slow_issue_message] => ) )
trustpilot	Array ( [to_email] => onlinejobs.ph+3d844ebf71@invite.trustpilot.com )
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replacemyself_secret_key	Kk1WpgTMkc4wBQOqC5rqCssdLhACKrsJeTtO1ywUkT4=
app	Array ( [app] => Array ( [command] => Array ( [map] => Array ( [OnlineJobs\Mailer\Command\SendEmailCommand] => OnlineJobs\Mailer\Handler\SendEmailHandler [OnlineJobs\Mail\Command\SendEmailCommand] => OnlineJobs\Mail\Handler\SendEmailHandler [OnlineJobs\Mail\Command\QueueEmailPendingCommand] => OnlineJobs\Mail\Handler\QueueEmailPendingHandler [OnlineJobs\Mail\Command\QueueJobEmailPendingCommand] => OnlineJobs\Mail\Handler\QueueJobEmailPendingHandler [OnlineJobs\Mail\Command\QueueUnapprovedEmailCommand] => OnlineJobs\Mail\Handler\QueueUnapprovedEmailHandler [OnlineJobs\Mail\Command\ProcessEmailQueueCommand] => OnlineJobs\Mail\Handler\ProcessEmailQueueHandler [OnlineJobs\Mail\Command\PutJobseekerEmailOnHoldCommand] => OnlineJobs\Mail\Handler\PutJobseekerEmailOnHoldHandler [OnlineJobs\Purchase\Command\RealEstateVaCourseCommand] => OnlineJobs\Purchase\Handler\RealEstateVaCourseHandler [OnlineJobs\Test\Command\HelloCommand] => OnlineJobs\Test\Handler\HelloHandler ) [middleware] => Array ( ) ) [providers] => Array ( [0] => OnlineJobs\Bus\BusServiceProvider [1] => OnlineJobs\Database\DbServiceProvider [2] => OnlineJobs\Mailer\MailerServiceProvider [3] => OnlineJobs\Support\SupportServiceProvider [4] => OnlineJobs\Employer\ServiceProvider [5] => OnlineJobs\Jobseeker\ServiceProvider [6] => OnlineJobs\Mail\ServiceProvider [7] => OnlineJobs\Postal\ServiceProvider [8] => OnlineJobs\Queue\ServiceProvider [9] => OnlineJobs\Courier\ServiceProvider [10] => OnlineJobs\Job\ServiceProvider [11] => OnlineJobs\Purchase\ServiceProvider ) ) )
meta	Array ( [facebook] => Array ( [input] => 1 [connect] => 2 [timezone] => 3 [url] => 30 [id] => 31 [photo] => 32 [name] => 33 [email] => 34 [review] => 35 ) [trust] => Array ( [government_id] => 4 [utility_bill] => 5 [selfie_photo] => 6 [profile_picture] => 7 [phone_number] => 8 [facebook] => 9 ) [verify] => Array ( [profile_picture] => 10 [government_id] => 11 [selfie_photo] => 12 [utility_bill] => 13 [address] => 14 [name] => 15 [reviewed] => 16 [government_group] => 28 [address_group] => 29 [mobile] => 38 ) [address] => Array ( [complete] => 17 [room_unit_no] => 20 [house_no] => 21 [street] => 22 [subdivision] => 23 [barangay] => 24 [city] => 25 [province] => 26 [postcode] => 27 ) [reviewed] => Array ( [similar_names] => 1 ) [name] => 18 [phone] => 19 [sms_verification_code] => 36 [resend_verification_code] => 37 [address_read] => 39 [first_name] => 100 [middle_name] => 101 [last_name] => 102 [edit] => Array ( [government_id_group] => 40 [address_group] => 41 [mobile_group] => 42 ) [salary_re_entry] => 103 [id_proof_recalibrate] => 104 [email] => 44 [mobile_verification_type] => 45 )
honeypot	Array ( [name_field] => my_name [enabled] => 1 )

HTTP_ACCEPT	/
HTTP_USER_AGENT	Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)
HTTP_CONNECTION	Upgrade
SERVER_PORT	80
SERVER_NAME	v1.stage.onlinejobs.ph
REMOTE_ADDR	127.0.0.1
SERVER_SOFTWARE	Apache/2.4.58 (Ubuntu)
HTTP_ACCEPT_LANGUAGE
SCRIPT_NAME	/index.php
REQUEST_METHOD	GET
HTTP_HOST
REMOTE_HOST
CONTENT_TYPE
SERVER_PROTOCOL	HTTP/1.1
QUERY_STRING
HTTP_ACCEPT_ENCODING	gzip, br, zstd, deflate
HTTP_X_FORWARDED_FOR	216.73.216.196
HTTP_DNT