Data Scientist

With 75 years of experience, our focus is on helping the most vulnerable children overcome poverty and experience fullness of life. We help children of all backgrounds, even in the most dangerous places, inspired by our Christian faith.

Come join our 33,000+ staff working in nearly 100 countries and share the joy of transforming vulnerable children’s life stories!

Key Responsibilities :

Job Purpose

We are seeking a dynamic individual to fill the role of Data Scientist. They will be a vital part of our data-driven decision-making process and moving WV into a more data-centric organization. They will play a crucial role in transforming raw data into actionable insights, developing machine-learning models, and building robust data pipelines to support our data-driven decision-making process. They will be working on Partnership Data Capability across all different data sources from Our Impact Our Story (OIOS) including Sponsorship, Vision Fund, and Safeguarding, Finance, Grants, Disaster Management, Advocacy, Faith & Development and all other sectors. They will focus on data analytics & data science focusing on business analytics, predictive analytics, machine learning, artificial intelligence, mobile, and AR / MR applications.

Key Responsibilities

Data Analysis and Exploration :

Analyze complex datasets to uncover trends, patterns, and insights.

Conduct exploratory data analysis to understand the data thoroughly.

Dive deep into a wide range of data (OIOS, Horizon, Grants, DM, FRSC, VFI, Advocacy, Faith & Development, and Sectors etc.) to identify opportunities and recommend solutions.

Support ongoing technology evaluation process and proof of concept projects.

Machine Learning and Modeling :

Develop and implement machine learning algorithms and models for predictive and prescriptive analytics.

Evaluate model performance, fine-tune models, and iterate to improve accuracy.

Create advanced analytic models using statistics, AI, machine learning, and deep learning methodologies.

Create clear and informative data visualizations and reports using tools like Tableau, Power BI, or Matplotlib.

Communicate data findings to non-technical stakeholders effectively.

Data Preprocessing and Cleaning :

Prepare data for analysis by handling missing values, outliers, and data quality issues.

Implement data transformation and feature engineering techniques.

Run regular tests and statistical analysis, draw conclusions on the accuracy of the data.

Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Work closely with data engineers to ensure data pipelines are efficient and reliable.

Identify unexplored data opportunities for the business to unlock and maximize the potential of digital data within the organization.

Data Integration :

Collaborate with other data scientists / data analysts across the partnership to provide them with clean and structured data.

Perform optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, R, SQL, Salesforce, and AWS technologies.

System Documentation :

Maintain comprehensive documentation of data integration & engineering processes, configurations, and procedures.

Stay up-to-date with the latest developments in data science, machine learning, and analytics techniques.

Share knowledge and best practices with the team.

Required Knowledge & Qualifications

5–7 years of professional industry experience in quantitative analysis.

Minimum 4+ years of hands-on experience as a Data Scientist and / or Data Analyst in real-time projects.

Proven experience managing complex data acquisition tools and platforms.

Bachelor’s or Master’s degree in Data Science, Computer Science, Information Technology, Statistics, Applied Mathematics, or a related quantitative field.

Certifications in Data Analytics or Data Science are required.

Effective written and verbal communication in English.

Preferred Knowledge and Qualifications

Certifications in Salesforce, AWS, or Azure are advantageous.

Experience with statistical modeling, machine learning, deep learning, optimization, and other DS techniques.

Experience in modeling, validating, importing, cleaning, and transforming data with the purpose of extracting insights for decision-making purposes.

Experience building and deploying machine learning models (e.g., KNN, Decision Trees, Clustering, Neural Networks).

Proficiency in statistical techniques (e.g., regression, distributions).

Expertise in designing and testing experiments.

Experience using statistical computer languages (R, Python, Matlab, SPSS etc.) to manipulate data and draw insights from large data sets. Preferred : Strong knowledge of Python.

Experience with AI / ML methods using Python or R.

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Hands-on experience in extraction, mining, and transformation and presentation of data on various reporting tools like Power BI, Tableau, etc.

With 75 years of experience, our focus is on helping the most vulnerable children overcome poverty and experience fullness of life. We help children of all backgrounds, even in the most dangerous places, inspired by our Christian faith.

Come join our 33,000+ staff working in nearly 100 countries and share the joy of transforming vulnerable children’s life stories!

Key Responsibilities :

Job Purpose

We are seeking a dynamic individual to fill the role of Data Scientist. They will be a vital part of our data-driven decision-making process and moving WV into a more data-centric organization. They will play a crucial role in transforming raw data into actionable insights, developing machine-learning models, and building robust data pipelines to support our data-driven decision-making process. They will be working on Partnership Data Capability across all different data sources from Our Impact Our Story (OIOS) including Sponsorship, Vision Fund, and Safeguarding, Finance, Grants, Disaster Management, Advocacy, Faith & Development and all other sectors. They will focus on data analytics & data science focusing on business analytics, predictive analytics, machine learning, artificial intelligence, mobile, and AR / MR applications.

Key Responsibilities

Data Analysis and Exploration :

Analyze complex datasets to uncover trends, patterns, and insights.

Conduct exploratory data analysis to understand the data thoroughly.

Dive deep into a wide range of data (OIOS, Horizon, Grants, DM, FRSC, VFI, Advocacy, Faith & Development, and Sectors etc.) to identify opportunities and recommend solutions.

Support ongoing technology evaluation process and proof of concept projects.

Machine Learning and Modeling :

Develop and implement machine learning algorithms and models for predictive and prescriptive analytics.

Evaluate model performance, fine-tune models, and iterate to improve accuracy.

Create advanced analytic models using statistics, AI, machine learning, and deep learning methodologies.

Data Visualization :

Create clear and informative data visualizations and reports using tools like Tableau, Power BI, or Matplotlib.

Communicate data findings to non-technical stakeholders effectively.

Data Preprocessing and Cleaning :

Prepare data for analysis by handling missing values, outliers, and data quality issues.

Implement data transformation and feature engineering techniques.

Run regular tests and statistical analysis, draw conclusions on the accuracy of the data.

Collaboration :

Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.

Create data tools for analytics and data scientist team members that assist them in building and optimizing our product into an innovative industry leader.

Work closely with data engineers to ensure data pipelines are efficient and reliable.

Identify unexplored data opportunities for the business to unlock and maximize the potential of digital data within the organization.

Data Integration :

Collaborate with other data scientists / data analysts across the partnership to provide them with clean and structured data.

Perform optimal extraction, transformation, and loading of data from a wide variety of data sources using Python, R, SQL, Salesforce, and AWS technologies.

System Documentation :

Maintain comprehensive documentation of data integration & engineering processes, configurations, and procedures.

Continuous Learning :

Stay up-to-date with the latest developments in data science, machine learning, and analytics techniques.

Share knowledge and best practices with the team.

Required Knowledge & Qualifications

5–7 years of professional industry experience in quantitative analysis.

Minimum 4+ years of hands-on experience as a Data Scientist and / or Data Analyst in real-time projects.

Proven experience managing complex data acquisition tools and platforms.

Bachelor’s or Master’s degree in Data Science, Computer Science, Information Technology, Statistics, Applied Mathematics, or a related quantitative field.

Certifications in Data Analytics or Data Science are required.

Effective written and verbal communication in English.

Preferred Knowledge and Qualifications

Certifications in Salesforce, AWS, or Azure are advantageous.

Experience with statistical modeling, machine learning, deep learning, optimization, and other DS techniques.

Experience in modeling, validating, importing, cleaning, and transforming data with the purpose of extracting insights for decision-making purposes.

Experience building and deploying machine learning models (e.g., KNN, Decision Trees, Clustering, Neural Networks).

Proficiency in statistical techniques (e.g., regression, distributions).

Expertise in designing and testing experiments.

Experience using statistical computer languages (R, Python, Matlab, SPSS etc.) to manipulate data and draw insights from large data sets. Preferred : Strong knowledge of Python.

Experience with AI / ML methods using Python or R.

Advanced working SQL knowledge and experience working with relational databases, query authoring (SQL) as well as working familiarity with a variety of databases.

Hands-on experience in extraction, mining, and transformation and presentation of data on various reporting tools like Power BI, Tableau, etc.

Applicant Types Accepted :

Local Applicants Only

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