Data Scientist / Data Analytics Resume Sample
Kristoffer Sawayn
8154 Friesen Shores,
New York,
NY
+1 (555) 468 0907
Work Experience
Analytics Senior Data Scientist / Architect
11/2015
-
PRESENT
New York, NY
- Research on state-of-art statistical analysis techniques to continuously improve Predictive Analytics team’s competence within the analytics industry
- Extending company’s data with third party sources of information when needed
- Experience in the field of advanced analytics and data mining
- Demonstrated research project/program management experience is desired
- Collaborate and work closely with cross-functional business partners across Finance, Product, Engineering, Sales, and Product Marketing to key unanswered questions about revenue products
- Create meaningful presentations and analyses that tell a “story” focused on insights, not just data
- Be fast-moving and able to execute quickly on analyses; understand the 80–20 rule
Data Scientist, Advanced Analytics
11/2008
-
10/2015
Phoenix, AZ
- Experience in manipulating both structured and unstructured large data sets through statistical/numerical languages (e.g. SAS, Python, R)
- Intermediate understanding in Math and Statistics (e.g. Linear Algebra, Hypothesis Testing, Regression, Bayesian Inference)
- Retrieve, prepare, and process a rich data variety of data sources such as social media, news, internal/external documents, emails, financial data, and operational data
- Analyze and model structured data and implement algorithms to support analysis using advanced statistical and mathematical methods from statistics, machine learning, data mining, econometrics, and operations research
- Utilize a diverse array of technologies and tools as needed, to deliver insights, such as R, SAS, Python, Spark, Hadoop, Qlikview, and Tableau
- Deep experience in extracting, cleaning, preparing, and modeling data; command-line scripting, data structures, and algorithms; and working in a Linux environment
- Translate engagement objectives to a project plan with milestones, and resource/technology requirements, and teach, lead, and manage projects to successful execution
- Turn statistical and computational analysis into user-friendly graphs, charts, and animation. Enable those who aren’t professional data analysts to effectively interpret data. Ability to communicate results and educate others through reports and presentations
- Use predictive analytics and data mining to solve complex problems and drive business decisions
Data Scientist Student for Advanced Analytics
03/2003
-
10/2008
Philadelphia, PA
- Synthesize methodology and data into actionable revenue strategy, and communicate findings to key business partners and company leadership/management
- Create the analytics to leverage known, inferred and appended information about individuals to facilitate the right content, at the right time, across a guest’s planning, shopping, fulfillment and on-property experience
- Work as a strong contributing member of our data science team by building sophisticated predictive analytics capabilities for the Research Division
- Work with business stakeholders to understand, gather and document business requirements and build appropriate analytics to ensure business objectives are met in a timely manner
- Create visualization applications (charts, tables, graphs, etc,) for sharing findings with business stakeholders
- Adherence to best-in-class Data Mining process (CRISP) and creation of documents for compiling entire project lifecycle
- Leverage ‘big data’ native to Online Marketing to enhance and extend Marketing insight
- Development Experience in scripting language (e.g. Python, SQL)
Education
Neumont University
1998 - 2003
Science's Degree in Computer Science
Professional Skills
- Strong personality and excellent communication skills (deliver information to large audience & top management)
- Demonstrated leadership, initiative, analytical skills, and sound business acumen including the ability to understand and analyze all types of data
- Software development and excellent programming skills (e.g. C#, C++, Java, Python, R, etc.)
- Advanced programming skills in Python
- Advanced programming skills in at least one of Python or Java
- Relevant experience as a strong contributor on a data science team using predictive modelling technics
- Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc
How to write Data Scientist / Data Analytics Resume
Data Scientist / Data Analytics role is responsible for java, programming, database, languages, python, design, finance, integration, telecommunications, analysis.
To write great resume for data scientist / data analytics job, your resume must include:
- Your contact information
- Work experience
- Education
- Skill listing
Contact Information For Data Scientist / Data Analytics Resume
The section contact information is important in your data scientist / data analytics resume. The recruiter has to be able to contact you ASAP if they like to offer you the job. This is why you need to provide your:
- First and last name
- Telephone number
Work Experience in Your Data Scientist / Data Analytics Resume
The section work experience is an essential part of your data scientist / data analytics resume. It’s the one thing the recruiter really cares about and pays the most attention to.
This section, however, is not just a list of your previous data scientist / data analytics responsibilities. It's meant to present you as a wholesome candidate by showcasing your relevant accomplishments and should be tailored specifically to the particular data scientist / data analytics position you're applying to.
The work experience section should be the detailed summary of your latest 3 or 4 positions.
Representative Data Scientist / Data Analytics resume experience can include:
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL, etc
- Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets
- Assess the effectiveness and accuracy of new data sources and data gathering techniques
- Experiences as a software engineer, data engineer or data scientist
- Work experience in a similar field
- Knowledge of different statistical techniques: temporal series, machine learning, clustering ..
Education on a Data Scientist / Data Analytics Resume
Make sure to make education a priority on your data scientist / data analytics resume. If you’ve been working for a few years and have a few solid positions to show, put your education after your data scientist / data analytics experience. For example, if you have a Ph.D in Neuroscience and a Master's in the same sphere, just list your Ph.D. Besides the doctorate, Master’s degrees go next, followed by Bachelor’s and finally, Associate’s degree.
Additional details to include:
- School you graduated from
- Major/ minor
- Year of graduation
- Location of school
These are the four additional pieces of information you should mention when listing your education on your resume.
Professional Skills in Data Scientist / Data Analytics Resume
When listing skills on your data scientist / data analytics resume, remember always to be honest about your level of ability. Include the Skills section after experience.
Present the most important skills in your resume, there's a list of typical data scientist / data analytics skills:
- Strong experience in data science with the focus on data mining, machine learning and applied statistics
- Experience visualizing/presenting data for stakeholders using: Tableau, MicroStrategy, etc
- Experience using and implementing visualization tools like D3, Microsoft Power BI or Tableau
- Experience working with and creating data architectures
- Experience querying databases and using statistical computer languages: R, Python, SLQ, etc
- Experience producing research reports
List of Typical Experience For a Data Scientist / Data Analytics Resume
1
Experience For Data Scientist, Advanced Analytics Resume
- Excellent Relational SQL database skills and demonstrate understanding in at least one programming language such as Java, C++ or C#
- Firsthand experience in data analysis and data manipulation with any of the following software: SQL Server, SAS, IBM SPSS
- Experience in developing SSIS packages
- Knowledge of big data technologies including batch and streaming processing and cloud computing (e.g. Hadoop, Spark, Flink, etc.)
- The team is fully transverse as we are working with production, marketing, CRM, media, licensing, sales and finance
- Deep understanding of statistical and predictive modeling concepts and recommendation and optimization algorithms
- Develops and manages relationships across the entire client base, discussing benefits and value at Board level
- Accuracy of models (statistics of fit) by tracking predictions vs. actual patterns
- Show ability to translate findings into clear insights and then communicate verbally and through compelling written documents
2
Experience For Analytics Senior Data Scientist / Architect Resume
- Openness to extensive international traveling
- Employ the appropriate algorithms to discover patterns of risks, abuse, and help reduce bad debt
- Experience in business analytics, forecasting or business planning with emphasis on analytical modeling, quantitative reasoning and metrics reporting preferably from an internet environment
- Experience in machine learning and statistical techniques such as classification, clustering, regression, statistical inference, collaborative filtering, and natural language processing, experimental design, social networking analysis, feature engineering etc
- Work with large, possibly unstructured datasets
3
Experience For Data Scientist, Predictive Analytics Resume
- Generate statistical models for a variety of phenomena
- Measure & communicate analytic results & impact of analytics model
- Organizes and shapes an engagement team’s strategy to drive success
- Consults and shapes development of the client’s approach to identifying and managing risks and assumptions and for realizing benefits at a department level
- Commercially shapes deals based on business benefit to client rather than actual cost to complete (value based pricing), identifying risk/reward opportunities and developing business cases to work with clients in new and different ways to mutual benefits
- Advises at Board level on Management of Change (MOC) strategies and implementation plans
- Consults on governance, strategy and transformation, not just operations
4
Experience For Senior Data Scientist, Advanced Analytics Resume
- Leads complex MOC initiatives
- Design, develop, and implement advanced analytical architectures to enable business insights
- Code, Analyze and Interpret advanced analytical methods applied to data from various sources
- Consult with business teams on the appropriate selection, utilization, and interpretation of advanced statistical methodologies
- Communicate and educate technical and non-technical employees on advanced analytics
- Coordinate and interface with appropriate management, communicate with industry and functional groups educating technical and non-technical employees on advanced analytics
- Develop and maintain internal process and project documentation related to projects
- Define data needs and evaluate data quality for applicability to posed problems
5
Experience For People Analytics & Research Data Scientist Resume
- Use statistical modeling, machine learning and numerical optimization to discover and leverage patterns in data using...[Time Series Analysis, Classification Algorithms, Clustering, Regressions, Recommender Systems, Linear/Nonlinear Optimization, Monte-Carlo simulation, text mining, natural language processing]
- Create features and develop models beyond standard toolset libraries to meet unique business challenges
- Interpret and communicate findings and insights from the data to business partners
- Build different models which provide insights for teams across the organization including, but not limited to our brand, CRM, production, and executive management teams
- Leverage or develop innovative data mining and machine learning methods to solve novel and diverse business problems
- Collaborate with business partners to determine how data can improve decision making
- Develop prototype systems that can be further be developed and deployed within Global Banking platforms
6
Experience For Data Scientist Data Analytics & Visualization Resume
- Mine and analyze data from various banking platforms to drive optimization and improve data quality
- Master or upper in computer science or mathematics
- Proficiency in SQL or HiveQL
- Manage timelines and business sponsor expectations
- Build relationships and trust with key stakeholders
- Supervise the work of junior team members
7
Experience For Data Scientist Iv-prepaid Analytics Resume
- Explore and when necessary transform structured and unstructured data from multiple sources to facilitate analyses
- Actively participate in a peer review process for new and existing mining and modeling techniques giving and receiving constructive feedback to constantly improve their application
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications
- Someone with 5-7 years of experience manipulating data sets and building statistical models, has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field, and is familiar with the following software/tools
- Successful prototype to demonstrate value proposition or to mitigate technical or data risks
- Strong commercial acumen and ability to tie analytics to drive business outcomes
- Statistical programming in tools like R, Python, SAS, SPSS, MATLAB,.
8
Experience For Data Scientist Program Development Analytics Resume
- Knowledge of big data platforms as Hadoop, Cassandra, MongoDB, Hive, Spark ..
- Applying cross industry these capabilities of different business needs: customer intelligence, marketing intelligence, fraud, process optimization, text mining, real time decision engine, internet of things,..
- Engage with sponsors in business units, functions, or Senior Management as well as with data subject matter experts to identify requirements, understand data collection work practices, and acquire data
- Perform data analysis to reveal, compile and present new insight
- Collaborate with business sponsors throughout development process in order to produce a valuable analytical solution
9
Experience For Data Scientist, Marketing Analytics Resume
- Lead all phases of project data mining lifecycle: data preparation, cleansing, modeling and fine-tuning to build accurate, robust, and reliable statistical result
- Spearhead technical aspect of model deployment and work with IT and Solution Architects to ensure the full integration of the model
- Promote your project and build new connections within and outside our business
- Successful solution deployment and adoption
- Realization of agreed upon business’s KPIs set for the analytical project
- Develop & implement models to support MBPS’ business pillar initiatives
- Develop & implement models to support business pillar initiatives
- Proven experience in one or more of the following financial processing area’s on SAP: Procure to Pay (PTP), Order to Cash (OTC), Human Resourcing (HR), Financial Statement Close Process (FSCP)
- Experience in SAP risk and control analytics covering the areas of Access and Change Management
10
Experience For Data Scientist, Insurance Analytics Resume
- Data analysis skills with strengths in drilling into underlying databases for discovery and identifying opportunities and trends and translating these into understandable and meaningful business outputs
- Proven experience in SAP, in particular – but not limited to - in one or more of the following financial processing area’s on SAP: Procure to Pay (PTP), Order to Cash (OTC), Human Resourcing (HR), Financial Statement Close Process (FSCP)
- Publishing of results, creation of intellectual property and work in committees
- Expertise in analyzing large, multi-dimensional datasets with a variety of tools, such as R, MATLAB, SPSS or SAS. Familiarity with SQL, Python, Java and C/C++
- Build-up a team of Data Scientists/Engineers
- Subject matter expertise in specification of Analytics architectures and tool chains for specific business challenges
- Strong knowledge of data mining / predictive modeling tools such as TD Aster, SAS, R, Python or Statistica as well as proficient in SQL and exposure to Teradata & Oracle
List of Typical Skills For a Data Scientist / Data Analytics Resume
1
Skills For Data Scientist, Advanced Analytics Resume
- Experience in advanced analytics including modeling work in SAS, R, Minitab, Python, and SQL
- Five or more years’ experience in advanced analytics, preferably including modeling work in SAS, R, Minitab, Python, and SQL
- Experience producing research reports and (ideally) predictive models
- Experience with large data sets and distributed computing tools (Map/Reduce, Hive, etc.)
- Professional experience with predictive statistical models or numerical optimization, and working with typical data used in such analyses
- Flexible and willing to learn from other people’s experiences
2
Skills For Analytics Senior Data Scientist / Architect Resume
- Possess the ability to operate in uncertain and changing circumstances
- Experienced in Reporting and Business Intelligence (Tableau, Qlikview etc.)
- Strong disdain for bad complexity
- Excellent team player; ability to work across functions at various levels and influence without authority
- Strong execution and follow through
3
Skills For Data Scientist, Predictive Analytics Resume
- Solid knowledge of Computer Science and Statistics
- Experience with Python data analysis tools (numpy/pandas/scikit-learn) and SQL
- Experience with data analysis tools (R, numpy/pandas/scikit-learn) and SQL
- Experience with 3rd party modeling tools and programming languages (e.g. R, python)
- Willing to challenge ‘old habits’ and able to see new opportunities,
- Willing to work Capacity to work 2.5 days a week in parallel to the studies
- Uncover persistent biases by analyzing trading behavior using data science techniques
- Work with large datasets and distributed computing tools for analysis, data mining and modeling
- Contribute to coding optimizer and pre/post-processing routines in Python pandas
4
Skills For Senior Data Scientist, Advanced Analytics Resume
- Interest in working in a fast-paced, frequently-changing environment
- Lead data analysis engagements, including providing guidance and supervision to other members of the team
- Formulate portfolio optimization algorithms, ranging from constrained equal weight optimization to Black-Litterman optimization
- Contribute to visualizing results in reports and/or Tableau
- Black belt certification, being Scrum/Agile and/or Prince2 certified is an advantage
- Understands approaches to customer segmentation, advanced analytics, and predictive modeling
- Fluency with at least one scripting language such as Python or Perl
5
Skills For People Analytics & Research Data Scientist Resume
- Distributed Computing and Algorithm Optimization
- Scikit-learn, MLLib and other Machine Learning libraries
- Financial Engineering knowledge and familiarity with risk and regulatory data
- Proficient in one or more programming languages (Python, R, Scala)
- Comfortable manipulating data in one or more of (SQL, Hive, Impala, Pig, Spark)
6
Skills For Data Scientist Data Analytics & Visualization Resume
- Familiarity with Online Marketing
- Draw relevant inferences and insights from data including, identification of trends and anomalies
- Overall engagement portfolio potential $20M and above and/or Service-based consulting account potential total contract value (TCV) $50M
- Lead advanced analytics research tackling some of the most important questions / solutions within NCR
- Highly organized, analytical thinker
- Run and interpret the results of models - distill large amounts of complex, detailed information into clear, summaries and recommendations
- Contribute in the development of analytics methodology, tools, and measurement
- Identify, acquire and use large volumes of data to provide incremental business value through creation of new models and algorithms that help the Internal Audit group execute Audits more efficiently and allow management to identify emerging risks
7
Skills For Data Scientist Iv-prepaid Analytics Resume
- Experience with large database platforms (e.g., Teradata, Hadoop, Oracle, Cassandra, etc.) or other similar platforms
- Experience with Business Requirements Analysis and Business Intelligence
- Experience in doing agile software development in a team
- Experience in one of the following fields: Operations Research, Data Analytics, Mathematical Optimization, Algorithmics or Big Data
- Experience in Software Engineering and System Architecture
- Experience in Matlab/R/Python or other vector based language
- Data-Science experience -an advantage
- Equivalency to Ph.D. defines as ability to hypothesize, design own experiments, draw conclusions and provide direction
- M.S. Analytics, Data Science, Statistics, Math, or related quantitative field
8
Skills For Data Scientist Program Development Analytics Resume
- Translate data into meaningful value propositions for business partners in order to facilitate understanding. Provide accurate and actionable business intelligence reporting
- Professional experience with predictive statistical models or numerical optimization, and working with typical data used in such analyses
- A student for M.Sc./Ph.D. in an academic field relevant to machine learning or image processing such as computer science, mathematics, statistics, and electrical engineering
- Academic or hands on experience with machine-learning algorithms and techniques
- Hands-on experience of combining all of the above disciplines
- Experience working in a cloud environment (Azure or AWS)
9
Skills For Data Scientist, Marketing Analytics Resume
- Professional experience with predictive statistical models or numerical optimization, and working with typical data used in such analyses
- B.S in Computer Science, Statistics, Engineering, or Math
- Knowledge of two or more of the following: SAS (base SAS, SAS Enterprise Guide, SAS Forecast Studio, or SAS OR), R, Python
- Work with engineering team to implement strategies into production
- Knowledge of big data technologies for batch and stream processing (e.g. Hadoop, Spark, Flink, etc.), local and in the cloud
10
Skills For Data Scientist, Insurance Analytics Resume
- The position is based in Petach Tikva or Haifa
- Experience with full cycle of analytical model deployment: Proven track record of solving and realizing value from Machine Learning and Optimization Problems
- Experience with big data tools such as Hadoop, Hive, Spark, etc
- Visualization tools: Power BI, Tableau, or any other
- Formulate research problems and define a research roadmap
List of Typical Responsibilities For a Data Scientist / Data Analytics Resume
1
Responsibilities For Data Scientist, Advanced Analytics Resume
- Proactive, able to prioritize, quality-minded, performance oriented
- Master/PhD in Engineering, Economics or Sciences
- SAS and/or Python and/or R expert
- High proficiency in English + French and / or Dutch
- Team player and open minded
2
Responsibilities For Analytics Senior Data Scientist / Architect Resume
- Conduct independent hands-on research and data analysis
- Work with business partners to articulate strategies and results
- Learn and implement behavioral economics methodologies
- Top Secret (TS/SCI) - Active
- Knowledge of French and English
3
Responsibilities For Data Scientist, Predictive Analytics Resume
- Excellent programming skills and software design knowledge using at least one programming language to bring data science from data to solution (e.g. C#, Java, Python, R, etc.)
- Practical experience in information visualization
- Deep understanding of data science and statistical analysis with experience building mathematical algorithms and machine learning models using tools like R, Python, MATLAB, or Stata
- Hands-on SQL experience
- Exposure with data mining and visualization techniques
- Proficiency with SQL and the ability to work with large data sets
- Knowledge of tools like Google Analytics, Tableau, Amplitude, and Treasure Data is a nice to have
4
Responsibilities For Senior Data Scientist, Advanced Analytics Resume
- Working knowledge in machine learning techniques such as Bayesian Methods, Clustering, Decision Trees, Linear and Non-Linear Programming, Random Forests, SVM, and etc
- Working knowledge of NLP techniques
- Familiarity with AWS and Qubole
- Highly collaborative, used to work in a consensus driven culture
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