Spirax Sarco

Data Scientist/Engineer

wejo

Connected vehicle data is transforming the way we live, work and travel. Wejo is at the forefront of this data explosion, enabling a wide range of businesses and governments to develop products and offerings that benefit peoples’ lives, drive revenue and power innovations.

Data Scientist

HACE

•	A start-up looking at leveraging data to improve child-labour situation in 3rd world countries as well to help supply-chain in modern world.
•	Collaboration and management of data scientists to ensure objective alignment
•	Identification of appropriate machine learning or statistical modelling methods to assess impact and correlation of cross-sectoral factors such as education, health, energy on child-labour.
•	Writing skeleton codes from data import to predictive analysis along with debugging issues.
•	NLP, Machine Learning, Python, SQL, Power BI, Tableau

•	Provided consultancy services to training providers in the apprenticeship sector for Level-4 Data Analysis apprenticeships
•	Created bespoke technical training material covering data analysis, predictive analysis and visualisation using tools such as python, R, SQL, Tableau and PowerBI, Azure Machine Learning Studio and Amazon Sagemaker
•	Liaison with employers to understand business, department and existing systems to align business and learning goals 
•	Supported delegates in using CRIPS-DM methodology to frame business issues into analytical problems and on-going supervision with both theoretical and practical knowledge

Data Analytics Trainer/Content Creator/Consultant

Kalibrate

Data Analytics Consultant

Transport Systems Catapult

Responsibilities:

- Liaison with consortium members and team members for idea sharing, discussions on methodology and implementation along with selection of appropriate tools
- Understanding the problem. Evaluation of current solutions and limitations
- Research on state-of-art Mathematical, Machine-Learning and Statistical techniques
- Worked with tools such as R, Python, SQL, Hive, Tableau and MATLAB

Achievements:

Worked & Contributed on numerous projects:

- Smart Clean - https://www.intouch-ltd.com/special-projects/
- CATCH - http://www.travelai.info/catch-workshop.html
- Department for Transport - Submitted a recommendation report for DfT (Department for Transport) regarding inclusion of a highways layer to the OS maps for fixed highways assets and car parks in collaboration with DfT, GeoPlace and Ordnance Survey.
- Station Innovation - A project to optimize passenger occupancy at platforms for train stations across the UK.

AstraZeneca

Project Title: Using Machine Learning To Gain Insights into Cancer

Conclusion: An interesting triangular interaction was identified between haematology, blood chemistry & vitals of patients. The results were presented to a studious panel of statisticians, clinicians and analysts. On the technical side, extensive data preparation and ensemble learning - Boosting was used.

DETAILS:

Objective 1: PREDICTION
Application of ensemble machine learning technique called GBM (gradient boosting machines) to predict the survival rate of breast cancer patients using pre-study observations of a clinical trial. 

Objective 2: FEATURE SELECTION
Identification of controllable features that can help in increasing the survival rate amongst breast cancer patients.

Objective 3: INTEGRATION OF CLINICAL TRIALS
Identify problems and complexities for integration of clinical trials to enhance the statistical power of analysis and reduce the variability in results across different clinical trials.

Objective 4: VALIDATION
Validate the findings for prediction and feature selection using a second clinical trial with similar characteristics.

Data: The data was extracted from ProjectDataSphere. ProjectDataSphere is a global platform for pharmaceutical companies to share clinical trials data (comparator arm only) for a multitude of cancer types to aid in finding a better cure.

Barclays Bank Plc

Project 1

Description: 
Automation of Dialler system to delete contact numbers with a predicted savings of approx. £0.5million per year to the bank. This study showed monetary as well as efficiency benefits and provided an option for an interim solution until the work on a permanent fix was completed. 

Problem: 
Time consumption for manual deletion of contact numbers from 3 different systems that was causing loss to the bank in terms of financial cost and confidence of employees and most importantly client satisfaction.

Data: 
A record of approx. one million observations were collated from sources including Excel sheets and SAS database.

Analysis: 

The following steps were carried out during the analysis

1. Aggregation of data from different sources to form a single cohesive data set
2. Filtering out relevant data based on the call disposition code. Exploratory analysis using tables and graphs to look at trends, extreme values and missing observations. Missing values were omitted from the data.

4. Formulation of financial loss with the help of different features like time on call, cost of call to the bank, average salary of employees based on grade. A breakdown summary was created for a weekly, monthly and yearly views. Comparison of financial gains with the proposed solution

5. The study involved liaison with departments including Resource Analysts, Macro Team, Support/Change Team and external supplier (Blue Prism) for Macros creation.

Project 2

I prepared quality reports for the team in Excel using Pivot tables to pinpoint individual parameters, highlighting below average performances on a weekly, monthly, quarterly and yearly basis. The reports highlighted the overall percentages of marks obtained/lost along with percentage breakdown of each individual area.

Collections & Recoveries Unit Manchester

BayShore Business Services LLC

Business Development Manager

Abacus Consulting

Team Leader

Dedicated data scientist experienced in working on research and complex commercial situations, elucidate hidden patterns and present discoveries to an array of audience. Adept at writing production quality code, descriptive and predictive analytics Including Visualisation, Statistical Testing, Statistical Modelling, Forecasting, Machine Learning, framing business issues into analytical use-cases. A team player accomplished in working with cross-functional teams, administering support and looking to make our society a better place to live by harnessing data. 

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