About Nima
About Me
I am a Data Scientist and Analytics Specialist (MSc Data Science) specializing in processing, cleaning, and structuring extremely large, complex, and messy datasets. I help organizations turn fragmented, multi-source raw data into high-performing automated pipelines and clear executive strategy.
Rather than relying on basic spreadsheet tools or standard database queries, I use custom Python scripts (Pandas, NumPy, Scikit-learn) to handle heavy data transformation, anomaly detection, and predictive modeling at scale.
Core Services & Capabilities
- Large-Scale Data Cleansing & Transformation: Writing advanced, memory-efficient Python scripts to parse, clean, and integrate high-volume, messy datasets into structured, audit-ready data models.
- Process & Pipeline Automation: Streamlining tedious, error-prone manual workflows into automated, repeatable Python pipelines.
- Predictive Analytics & Machine Learning: Applying statistical modeling, trend forecasting, and anomaly detection algorithms to extract insights from raw data streams.
- Data Visualization & Reporting: Connecting processed datasets directly into clean Power BI or Tableau dashboards for executive decision-making.
Technical Toolkit
- Core Stack: Python (Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn), R
- Specialties: Heavy Data Wrangling, ETL Scripting, Anomaly Detection, Machine Learning, Automation
- BI & Visualization: Power BI, Tableau, Excel
- Tools & Version Control: Jupyter Notebooks, Git, VS Code
Why Work With Me?
- Built for Complexity: Experienced in handling messy, unstructured, high-volume data sources that crush standard off-the-shelf tools.
- End-to-End Pipeline Delivery: From raw, chaotic input files to fully cleaned models and automated visual summaries.
- Mathematical & Practical Rigor: Master’s-level quantitative training combined with real-world experience handling critical enterprise data ensures total data integrity.
English
Native or bilingual
Remote only
Primarily works remotely
Experience
- NHSCFAData AnalystAugust 2025 - Today (1 year)London, United Kingdom
- Deliver comprehensive analytical services to support the prevention, detection, and investigation of economic crime across the NHS.
- Establishing reusable pipelines and reports to support the transition from proof of concept to BAU.
- Utilise SQL, Python, and PySpark to manage, cleanse, and aggregate complex and large national datasets for actionable fraud intelligence, contributing towards recovering £495M.
- Apply advanced statistical techniques to examine anomalies and patterns indicative of fraudulent activity.
- Collaborate with Data Scientists and the response team to define methodologies and produce reports.
- Ensuring data processes strictly adhere to GDPR, the Data Protection Act 2017, and the Freedom of Information Act.
- Conduct regular data quality audits and develop new ETL methodologies to improve efficiency.
- NHSSpecialist Biomedical ScientistSeptember 2017 - February 2024 (6 years and 5 months)London, United Kingdom
- Designed and implemented a Tableau dashboard, integrated with the lab's LIMS, to track specimen
- workflow and pinpoint areas of delay.
- Facilitated targeted interventions to expedite urgent samples, resulting in a 66% reduction in the lab's backlog and decreased overall turnaround time.
- Worked in multidisciplinary settings, communicating complex laboratory data and findings to clinical teams to inform diagnosis and treatment plans.
- Contributed to the interpretation of data for patient management, demonstrating strong analytical and collaborative skills.
Recommendations
Be the first to recommend Nima
Help this freelancer shine by sharing your experience working together.
These freelancer profiles also match your criteria
Agatha Frydrych
Backend Java Software Engineer
4.7
(3)
2
Baptiste Duhen
Fullstack developer
4.6
(4)
5
Amed Hamou
Senior Lead Developer
4
(2)
7
Audrey Champion
Web developer
4.3
(3)
4
Education
- MastersUniversity of Essex2026Through the MSc in Data Science program at the University of Essex, I developed advanced technical expertise at the intersection of computational statistics, advanced programming, and computer science. My post-graduate training focused heavily on leveraging the Python data ecosystem, specifically Pandas, NumPy, and Scikit-learn, to perform complex data wrangling, exploratory statistical analysis, and machine learning modelling on high-volume datasets. I mastered applying supervised and unsupervised algorithms, regression models, and classification techniques to solve non-linear problems and extract actionable patterns. Additionally, the curriculum emphasised handling large-scale, unstructured data sources, constructing efficient data transformation pipelines, and translating multidimensional statistical outputs into intuitive executive reporting and interactive dashboards. Combined with an independent computational research project, this training established a solid foundation in data integrity, mathematics, and automated analytics.
- BachelorsUniversity of Portsmouth2026During my BSc (Hons) at the University of Portsmouth, I established a foundation in quantitative methodology, empirical research design, and structured data analysis. My undergraduate training focused on evaluating complex datasets generated through observational and experimental studies, requiring systematic data cleaning, hypothesis testing, and statistical validation. Through coursework in bioanalytics, computational methods, and evidence-based research, I gained extensive experience in identifying pattern variations, managing measurement error, and translating raw experimental metrics into structured scientific findings. This undergraduate background developed my analytical knowledge, attention to detail, and ability to handle high-dimensional, multi-variable data, skills that directly informed my subsequent advanced data science training.