Amplytics Inc.
Senior Associate - Data and Analytics
Amplytics Inc., San Francisco, California, United States, 94199
As a Senior Associate in Data and Analytics, you will play a pivotal role in assisting consultants in providing comprehensive data-driven insights and solutions to our clients. You will be responsible for collecting, analyzing, and interpreting complex data sets to generate actionable recommendations. Your expertise in data analytics tools and techniques will contribute to the development and implementation of strategies aimed at optimizing business performance and driving growth. This role requires a strong analytical mindset, attention to detail, and the ability to communicate effectively with both internal teams and clients.
Key Responsibilities:
Data Collection and Processing:
Gather and organize large volumes of structured and unstructured data from various sources. Develop processes for data cleaning, validation, and transformation to ensure accuracy and consistency. Collaborate with consultants to identify data requirements and streamline data collection procedures.
Data Analysis and Interpretation:
Utilize advanced analytical tools and techniques to analyze complex data sets. Extract meaningful insights and trends from data to support decision-making processes. Perform statistical analysis and predictive modeling to identify opportunities and risks.
Reporting and Visualization:
Prepare clear and concise reports, dashboards, and presentations to communicate findings to stakeholders. Create data visualizations and interactive dashboards to facilitate understanding of key metrics and trends. Customize reports and visualizations based on client requirements and feedback.
Collaboration and Support:
Work closely with consultants to understand client objectives and project requirements. Provide support in developing data-driven strategies and solutions to address client challenges. Collaborate with cross-functional teams to integrate data analytics into business processes and decision-making frameworks.
Stay abreast of industry trends, emerging technologies, and best practices in data analytics. Identify opportunities for process improvement and optimization within the data analytics function. Proactively contribute ideas and suggestions to enhance the quality and efficiency of our data analytics services. Qualifications:
Requirements: Bachelor's degree in data science, Statistics, Mathematics, Computer Science, or related field. Master's degree preferred. 3+ years of experience in data analysis, data mining, or related roles. Proficiency in data analytics tools such as SQL, Python, R, or similar. Experience with data visualization tools (e.g., Tableau, Power BI) and statistical software (e.g., SPSS, SAS). Strong analytical skills with the ability to interpret complex data sets and draw actionable insights. Excellent communication skills with the ability to present findings and recommendations to both technical and non-technical audiences. Ability to work effectively in a collaborative team environment and manage multiple priorities simultaneously. Strong attention to detail and commitment to delivering high-quality work within deadlines. Preferred Qualifications: Experience in management consulting or advisory services. Familiarity with machine learning algorithms and techniques. Knowledge of big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., SAP, Salesforce, AWS, Azure). Certification in data analytics or related field (e.g., Certified Analytics Professional, Data Science Certification).
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Data Collection and Processing:
Gather and organize large volumes of structured and unstructured data from various sources. Develop processes for data cleaning, validation, and transformation to ensure accuracy and consistency. Collaborate with consultants to identify data requirements and streamline data collection procedures.
Data Analysis and Interpretation:
Utilize advanced analytical tools and techniques to analyze complex data sets. Extract meaningful insights and trends from data to support decision-making processes. Perform statistical analysis and predictive modeling to identify opportunities and risks.
Reporting and Visualization:
Prepare clear and concise reports, dashboards, and presentations to communicate findings to stakeholders. Create data visualizations and interactive dashboards to facilitate understanding of key metrics and trends. Customize reports and visualizations based on client requirements and feedback.
Collaboration and Support:
Work closely with consultants to understand client objectives and project requirements. Provide support in developing data-driven strategies and solutions to address client challenges. Collaborate with cross-functional teams to integrate data analytics into business processes and decision-making frameworks.
Stay abreast of industry trends, emerging technologies, and best practices in data analytics. Identify opportunities for process improvement and optimization within the data analytics function. Proactively contribute ideas and suggestions to enhance the quality and efficiency of our data analytics services. Qualifications:
Requirements: Bachelor's degree in data science, Statistics, Mathematics, Computer Science, or related field. Master's degree preferred. 3+ years of experience in data analysis, data mining, or related roles. Proficiency in data analytics tools such as SQL, Python, R, or similar. Experience with data visualization tools (e.g., Tableau, Power BI) and statistical software (e.g., SPSS, SAS). Strong analytical skills with the ability to interpret complex data sets and draw actionable insights. Excellent communication skills with the ability to present findings and recommendations to both technical and non-technical audiences. Ability to work effectively in a collaborative team environment and manage multiple priorities simultaneously. Strong attention to detail and commitment to delivering high-quality work within deadlines. Preferred Qualifications: Experience in management consulting or advisory services. Familiarity with machine learning algorithms and techniques. Knowledge of big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., SAP, Salesforce, AWS, Azure). Certification in data analytics or related field (e.g., Certified Analytics Professional, Data Science Certification).
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