• Use statistical modeling and machine learning to transform raw data into actionable information.
• Provide data-driven insights that empower business leaders to make informed decisions.
• Solve real-world challenges with data, working on problems ranging from operational optimization to enhancing the customer experience.

• What is the best method for imputing missing values in time series data?
• What is the root cause of this outlier, and how can we prevent similar outliers from occurring in the future?
• What is the optimal value for this hyperparameter, and how does it affect the performance of the model?
• What are the best visualization techniques to use for this dataset, and what insights can we glean from the resulting visualization?
• Can this dataset be compressed or transformed to reduce its size or dimensionality? What are the associated tradeoffs?

As a Data Analyst, you will have the opportunity to work in a variety of capacities, with duties that can vary depending on the company and even the specific team you work on. Whether you find yourself in a technical role or one that focuses more on data visualization and reporting, you’ll be a key player in driving business decisions through your expert analysis of data. 

In some Data Analyst roles, you’ll work closely with Data Scientists to prepare data for modeling by running preliminary analyses. This may involve using your skills in programming languages like R or Python, as well as your ability to query and collect data using tools like SQL. To succeed in this role, you’ll need to be well-versed in investigatory and exploratory data analysis techniques, including distribution fitting, univariate and multivariate analysis, anomaly detection, imputation techniques for missing data, and some machine learning techniques such as clustering and classifying.

In other Data Analyst roles, you may be responsible for creating mathematical and statistical models that are descriptive, diagnostic, predictive, or prescriptive in nature. As a Data Analyst, you’ll have the chance to develop your skills over time, with entry-level positions focused on visualization and descriptive modeling and more senior roles focused on advanced modeling.

Throughout your career as a Data Analyst, you’ll have the opportunity to learn continuously, as there are always new techniques, programming languages, visualization tools, and more to learn about.

Data Analyst; Analytics Analyst; Data and Reporting Analyst; Statistical Data Analyst; Business Data Analyst.

• Analyze business data to uncover trends that provide a competitive advantage.
• Transform complex information into actionable insights.
• Drive organizational success by leveraging advanced analytical techniques.

• Which data visualization techniques should we use to effectively communicate complex data to stakeholders and make it easier for them to spot trends and patterns?
• How can we use data blending techniques to combine data from different sources and gain a more comprehensive view of business operations?
• What are the most effective ways to measure the effectiveness of sales teams and use these insights to optimize sales strategies?
• How can we use KPIs such as defect density and mean time to repair to optimize software development processes and improve software quality?
• What are the most effective KPIs to measure marketing performance, such as click-through rates, cost per click, and conversion rates?

As a Business Intelligence Analyst, you’ll be responsible for turning business data into valuable and actionable insights that can be used by leaders across the organization to make informed decisions and take focused action. You’ll work closely with teams across the company, such as Sales, Finance, Project Management, and People Operations, to develop metrics and KPIs (Key Performance Indicators) that can be used to monitor operations and measure progress toward company objectives. 

Using an OKR-KPI framework (Objectives and Key Results - Key Performance Indicators), you’ll develop real-time indicators and metrics that are communicated through visual dashboards. This means you’ll need to be skilled at sourcing, collecting, and cleaning data, as well as using mathematical and statistical modeling techniques to conduct your analyses.  

There are many business intelligence platforms in use by companies that can automate parts of the data collection, analysis, and modeling process, so you don’t necessarily need advanced coding skills to be successful in this role. If you enjoy working with data, solving complex problems, and helping drive business success, working as a Business Intelligence Analyst could be a great fit for you.

Business Intelligence Analyst; Business Data Analyst; Strategic Business Consultant; Intelligence Analyst; Consultant - Business Intelligence.

• Forecast future trends and anticipate market dynamics.
• Develop and implement data-driven strategies that optimize business operations.
• Leverage the power of machine learning techniques to improve and automate business processes.

• What are the most effective ways to integrate data from different sources, such as sales, marketing, and customer service, to build more comprehensive predictive models?
• How can we use time-series forecasting techniques to predict future demand for products or services?
• How can we use natural language processing techniques to analyze customer feedback and extract insights that can inform business strategy?
• How can we use causal inference techniques such as propensity score matching or difference-in-differences to measure the impact of specific policies on business outcomes?
• What are the most effective ways to measure the impact of different pricing strategies and use these insights to optimize revenue?

As a Business Analytics Analyst, you’ll be focused on using analytical and modeling techniques to develop predictive models that help companies build more effective strategies and take preemptive action to avoid undesired outcomes. You’ll have a deep understanding of business processes and priorities, and you’ll work closely with decision makers to support their needs and solve specific business problems. 

In this role, you’ll work on forecasting problems such as building financial forecasts, demand forecasts, or forecasts regarding the availability of production inputs, such as raw materials. You’ll build and use predictive models to help companies make informed decisions and plan for the future. While advanced modeling and coding skills are usually required for this role, the requirements tend to be less technical than for working as a Data Scientist. Business Analytics Analysts also tend to be more focused on specific business areas or problems, whereas Data Scientists build models of many phenomena.

There is variance in the work that Business Analytics Analysts do, and in some cases it might overlap with that of Business Intelligence Analysts. In general, Business Intelligence Analysts focus on past states and current states, whereas Business Intelligence Analysts focus primarily on making forecasts. If you enjoy analyzing data and building predictive models that drive business success, this is a good role to explore.

Business Analytics Analyst; Analytics - Lead Analyst; Data Analytics Analyst; Consultant - Business Analytics; Sr Business Analyst - Insights.

• Develop and implement financial strategies that drive profitability and growth.
• Help companies manage risks and achieve their financial goals.
• Use financial modeling techniques to assess the financial performance of companies.

• What is the impact of changes in macroeconomic indicators, such as interest rates or inflation, on the financial performance of this investment?
• How can we apply scenario analysis to test the resilience of this company’s financials under various hypothetical or industry-specific events?
• How do we optimize our cash management strategy to minimize idle cash balances while ensuring sufficient liquidity to meet short-term obligations?
• How do we evaluate the financial impact of potential mergers and acquisitions, taking into account a range of variables such as market conditions, regulatory considerations, and operational synergies?
• How do we analyze and forecast interest rate movements to optimize our debt and investment strategies and minimize interest rate risk?

As a Financial Analyst, you’ll play a critical role in helping companies make informed decisions and achieve their financial goals. Whether you focus on reporting or forecasting, your work will involve analyzing financial data and interpreting trends to provide valuable insights to decision makers. 

If you specialize in reporting, you’ll be responsible for creating accurate, detailed reports that provide an assessment of the company’s current financial state. You’ll also use your analytical skills to investigate historical data and identify trends and patterns, and communicate your findings to leadership. You may also build real-time dashboards that allow decision makers to monitor key financial metrics in real-time.

As a forecasting-focused Financial Analyst, you’ll use historical data to build models that attempt to predict future financial outcomes. Your work will involve developing and testing capital allocation and risk mitigation strategies that will help the company achieve its financial goals. You may use tools like Excel, SQL, or Python to build and test your models, making this a more technical role.

No matter which type of Financial Analyst role you pursue, you will be a key player in the financial success of your organization. You’ll have the opportunity to work with a diverse group of stakeholders and make a real impact on the financial health of the company.

Financial Analyst; Data Analyst - Finance; Financial Planning Analyst; Revenue Analyst; Sr Analyst - Finance.

• Identify, assess, and model risks across diverse sectors, from economic conditions to regulatory changes.
• Build sophisticated models that simulate future scenarios and provide insights for decision making.
• Develop effective risk management strategies.

• What is the value at risk (VaR) of our portfolio, and how does it compare to our risk tolerance levels?
• How can we use Monte Carlo simulations to model potential scenarios and quantify the impact of different risk factors on our investments?
• What is the expected shortfall (ES) of this investment, and how can we use this metric to measure tail risk?
• What is the correlation between different assets in our portfolio, and how can we use this information to diversify our investments?
• How can we use machine learning techniques to identify emerging risks and opportunities in financial markets?

As a Risk Analyst, you’ll have the opportunity to model potential financial risks to a business and its investments, helping companies navigate complex financial conditions such as new regulations, climate events, geopolitical disturbances, and changes in foreign exchange rates. You’ll analyze data and build models to understand how investments could be impacted in different future conditions, using simulation and mathematical and statistical modeling to create actionable insights. 

Your work will also involve testing the effectiveness of various mitigation strategies against potential future conditions, such as insurance, diversification, hedging, or contingency plans. You’ll be an integral part of the financial sector, working in investment banks, insurance companies, reinsurance companies, or in finance departments in non-financial companies. 

To succeed in this role, you’ll need significant mathematical and statistical expertise, along with the ability to build quantitative models of complex events. You’ll analyze complex financial data to identify risks to portfolios, and you’ll have a strong understanding of financial markets and products. You’ll also need to remain up to date with financial regulations, making sure that your models and strategies comply with legal requirements. 

As a Risk Analyst, you’ll play a crucial role in helping companies make informed decisions and mitigate risks in a rapidly changing financial landscape.

Risk Analyst; Risk Management Analyst; Investment Risk Analyst; Portfolio Analyst; Financial Risk Analyst.

• Leverage data analysis to detect and prevent fraudulent activities.
• Uncover anomalies to identify suspicious behavior and fraud risks.
• Utilize advanced statistical modeling to develop predictive models for fraud detection.

• How can we identify false positives and false negatives in our fraud detection algorithms, and how can we adjust these algorithms to reduce our errors?
• How can we use machine learning algorithms to identify emerging patterns of fraudulent activity and proactively adjust our fraud detection models to account for these new patterns?
• How can we improve our ability to detect insider threats and other types of fraud that may involve collusion between employees or partners?
• What are the legal and ethical considerations that come into play when designing and implementing fraud detection models, and how can we ensure that our models are compliant with all relevant regulations and guidelines?
• How can we incorporate natural language processing and sentiment analysis into our fraud detection models to identify potential fraudsters who may be communicating through text-based channels?

As a Fraud Analyst, you’ll be on the front line in protecting companies from financial losses and reputational damage caused by fraudulent activity. Your role will involve monitoring customer and business behavior for any signs of fraudulent activity, using your skills in statistical analysis, predictive modeling, and machine learning techniques. You’ll also work with specialized fraud detection software and platforms to investigate instances of fraud or anomalies in financial statements. 

Fraud incidents are constantly evolving in nature, and those who commit fraud consistently develop new techniques. As a result, you’ll need to stay up-to-date on industry trends and be very creative in constantly looking for new ways to monitor fraudulent activity. This is a challenging and dynamic field that requires a strong analytical mind, attention to detail, and the ability to work quickly to respond to an ever-evolving landscape. 

You can work in a variety of industries, including financial services, utilities, telecoms, online gaming and betting platforms, insurance, healthcare, and retail. Your work will help protect these companies from financial losses, reputational damage, or legal liability. If you’re passionate about uncovering fraud and helping to create a safer business environment, this could be a great fit for you.

Fraud Analyst; Investigative Analyst; Fraud Investigator; Fraud and Waste Analyst; Fraud Monitoring Analyst.

• Gather and analyze data related to various sustainability metrics to assess performance and identify areas for improvement.
• Compare an organization’s sustainability initiatives and performance against industry standards and best practices to identify gaps.
• Contribute to the development and implementation of sustainability strategies that align with organizational goals and global sustainability standards.

• How can we further reduce our carbon footprint across all operations without compromising productivity?
• Which sustainable technologies offer the best return on investment for our company’s unique needs?
• What are the most significant regulatory changes on the horizon that could affect our sustainability strategy?
• Which areas of our business have the largest environmental impact, and how can we mitigate these effectively?
• How can we more accurately measure and report on our sustainability performance to reflect true progress?

As a Sustainability Analyst, you’ll analyze and interpret data related to sustainability, such as carbon emissions, energy consumption and efficiency, water usage, waste production, decarbonization of business operations, and supply chain sustainability. You’ll focus on the environmental and economic impacts of organizations and their operations. Your data analysis will relate to sustainability reporting frameworks and impact assessment methodologies, which will help you qualify and quantify sustainability performance. 

Specifically, you might calculate and analyze the carbon footprints of business operations, products, or services and identify areas for reduction of energy consumption. You might investigate the environmental practices of suppliers in a company’s supply chain to ensure they meet the company’s sustainability standards. You might develop and integrate circular economy principles, such as recycling, reuse, or resource recovery, into existing business models to minimize waste. Or, you might perform life cycle assessments on products to understand their environmental impact from production to disposal, identifying opportunities to mitigate negative impacts. 

Your analysis and reporting will be influenced by the regulatory environment as well as industry standards. You’ll need to keep current on relevant environmental regulations and sustainability reporting requirements to ensure compliance. You’ll also compare the organization’s sustainability performance against industry benchmarks to identify gaps, best practices, and areas for improvement. Your work will influence the development of sustainability strategies; you’ll develop and implement strategies that align with organizational goals as well as sustainability standards.

Sustainability Analyst; Sustainability Data Analyst; Analyst - ESG & Sustainability; Sustainability Data and Reporting Analyst; Sustainable Sourcing Analyst.