Samira Cole
Selected analysis / research portfolioManchester, UK

Samira ColeData analyst and researcher studying public systems and product behavior

Available for selected analysis and research collaborations

I examine how services behave over time, where a pattern changes, and what a team can responsibly conclude from the available sample.

Review selected analysesEmail Samira
01
Question
02
Method
03
Evidence
04
Meaning

Selected analyses

Start with the question. Keep the finding visible.

Each project connects method and context to a chart, written finding, and practical next question.

Analysis 01

After the Last Connection

Question

Where did late-evening reliability fall furthest across four fictional transit periods?

Trips within five minutes (%)

Reliability changes across the evening

Reliability changes across the evening A line chart falls from 91 percent before 19:00 to 69 percent after 22:00, with intermediate values of 88 and 82 percent. 91%Before 19:0088%19:00–20:3082%20:30–22:0069%After 22:00

FindingLate-evening services show the widest reliability gap in the synthetic sample.

Synthetic sample · 120 fictional scheduled trips · fixed seed HE-01

Layered bus and rail platforms connected by empty paths at a fictional evening transit interchange

Analysis and meaning

I grouped 120 synthetic scheduled trips into four time periods, compared the share arriving within five minutes, and checked whether the pattern persisted across route groups. The fictional sample shows the widest reliability gap after 22:00, suggesting that an operations review should begin with late connections rather than a network-wide average.

Analysis 02

Reading Room Demand

Question

Which service periods placed the most pressure on a fictional community library?

Demand index (0–100)

Combined demand by service period

  1. Morning54
  2. Midday72
  3. Weekday afternoon93
  4. Evening61

FindingWeekday afternoons carry the highest combined demand in the synthetic service index.

Synthetic sample · visits, room bookings, and help requests · fixed seed HE-02

Analysis and meaning

I combined a small synthetic visit count with room-booking and help-desk demand, then compared periods using one shared index. Weekday afternoons show the highest combined demand in the demo data, making staffing and room turnover a more useful next question than total daily visits alone.

Analysis 03

First Week Signals

Question

At which onboarding step did a fictional product sample lose the clearest share of new participants?

Retained participants (%)

Share reaching each onboarding step

  1. Account created100%
  2. Source connected78%
  3. First review completed48%
  4. Returned in week two36%

FindingThe clearest drop occurs between connecting a source and completing the first review.

Synthetic sample · 240 fictional onboarding records · fixed seed HE-03

Analysis and meaning

I defined four completion milestones, removed repeated test accounts, and compared the retained share at each step. The synthetic sample drops most sharply between connecting a source and completing the first review, directing the next qualitative study toward setup clarity rather than acquisition.

Analysis 04

Shade Between Stops

Question

How did shade availability vary along five segments of a fictional walking route?

Midday shade score / waiting score

Shade and waiting exposure by route segment

FindingThe two central segments combine the least shade with the highest waiting exposure in the synthetic observation grid.

Synthetic observation grid · five fictional route segments · fixed seed HE-04

Unbranded observation tools beside a shaded fictional public walking route

Analysis and meaning

I coded each route segment using an invented observation sample covering midday shade, seating, and crossing exposure. Two central segments combine the least shade with the longest waits in the demo, helping frame a follow-up site study without claiming a measured citywide heat effect.

Approach

Interpretation begins with a bounded question.

Portrait of Samira Cole in a thoughtful research workspace.

My work covers transport reliability, community services, product analytics, and public-space research. I define the question before choosing a chart, keep assumptions visible, and write the finding in plain language beside the analysis.

The portfolio structure separates method, evidence, interpretation, and limitations. That makes it easier for a reader to understand the contribution without needing access to a dashboard or private dataset.

Methods and capabilities

Analysis choices made explicit.

01

Analysis

Exploratory analysis

02

Research

Experiment design · Survey and service research

03

Tools

SQL and data modelling · Python analysis

04

Communication

Accessible data communication

Experience

Analysis, research, and communication.

2023 — Present

Data analyst and researcher

Independent practice

Frame, analyse, and communicate small studies for public-interest and product teams.

2020 — 2023

Research analyst

Civic Pattern Lab (fictional)

Prepared reproducible analyses, service-research summaries, and accessible charts for internal decisions.

Education

Research and analytical foundations.

2018 — 2020

MSc, Applied Social Data

Merefield Institute of Social Research (fictional)

Studied research design, statistics, data ethics, and public-interest communication.

Discuss an analysis, research question, or data story.

samira@example.com