The Himss Data Scientist interview guide, interview questions, salary data, and interview experiences.

Himss Data Scientist Interview Guide

Getting ready for an Data Scientist interview at Himss? The Himss Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:
<ul>
<li>Know what skills are necessary for Himss Data Scientist roles.</li>
<li>Gain insights into the Data Scientist interview process at Himss.</li>
<li>Practice real Himss Data Scientist interview questions.</li>
</ul>
Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Himss Data Scientist interview.


Getting ready for an Data Scientist interview at Himss? The Himss Data Scientist interview span across 10 to 12 different question topics. In preparing for the interview:

- Know what skills are necessary for Himss Data Scientist roles.
- Gain insights into the Data Scientist interview process at Himss.
- Practice real Himss Data Scientist interview questions.

Interview Query regularly analyzes interview experience data, and we've used that data to produce this guide, with sample interview questions and an overview of the Himss Data Scientist interview.
        

Overview

Himss Data Scientist Salary

We've gathered this data from parsing thousands of interview experiences sourced from members.

We've gathered this data from parsing thousands of interview experiences sourced from members.

Himss Data Scientist Interview Process

Let’s say that you’re working on a job recommendation engine. You have access to all user Linkedin profiles, a list of jobs each user applied to, and answers to questions that the user filled in about their job search.

Using this information, how would you build a job recommendation feed?

What problem can arise in job recommendation systems with regard to initial recommendations?

What problem can arise in job recommendation systems with regard to initial recommendations?

Job Recommendation

Imagine you are asked to build a machine learning model to decide new loan approvals for a
financial firm. You ask the data department in the company for a subset of data to get started
working on the problem. The data includes different features about applicants such as age,
occupation, zip code, height, number of children, favorite color, etc. You decide to build
multiple machine learning models to test out different ideas before settling on the best one.

How would you explain the bias-variance tradeoff with regards to
building and choosing a model to use?

Bias vs. Variance Tradeoff

Given a list of integers, find the index at which the sum of the left half of the list is equal to the right half. If there is no index where this condition is satisfied return -1.

Note: the number that lies on the index is calculated to the left side of the list.

Example 1:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1, 7, 3, 5, 6]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>equivalent_index(nums) -&gt; 2
</code></pre>

In this example, the sum of the elements to the left of index 2 (1 + 7) is equal to the sum of the elements to the right of index 2 (5 + 6).

Example 2:

Input:

<pre tabindex="0" class="chroma"><code>nums = [1,3,5]
</code></pre>

Output:

<pre tabindex="0" class="chroma"><code>equivalent_index(nums) -&gt; -1
</code></pre>

In this example, there is no index where the sum of the elements to the left is equal to the sum of the elements to the right.

The task is to write a function that takes a list of integers as input and returns the index at which the sum of the integers to the left of the index is equal to the sum of the integers to the right. If no such index exists, the function should return -1.

Find the Index with Equal Left and Right Sum

Himss Data Scientist Interview Questions

We are seeking a Data Scientist for our client in New York City, NY (10048) for a full-time employee role. The candidate needs to be proficient in data engineering, predictive modeling, and reporting, with expertise in data visualization, machine learning techniques, Python, Azure, and SQL databases to support investment decision-making and portfolio management. This role will primarily be focused on driving reporting and analytics for our large real estate investment portfolio using public and private datasets. The ideal candidate is a self-starter and interested in working in a dynamic, fast changing environment. Key Responsibilities:<ul><li>Data Engineering:</li><li>Design, build, and maintain scalable data pipelines using Azure and other cloud-based tools to ingest, clean, and process large datasets from multiple sources (market data, accounting systems, analyst models).</li><li>Ensure data integrity and availability for investment analysis and reporting.</li><li>Data Modeling & Analytics:</li><li>Develop and implement models to assess credit risk, forecast asset pricing, and analyze fixed income securities.</li><li>Use Python for statistical analysis, predictive modeling, and automation of analytical workflows.</li><li>Reporting & Visualization:</li><li>Generate and automate reports that provide insights into portfolio performance, risk exposure, and market conditions.</li><li>Collaborate with portfolio managers to deliver actionable data-driven insights through clear visualizations and dashboards.</li><li>Collaboration & Stakeholder Engagement:</li><li>Work closely with investment teams to translate complex data analysis into investment strategies and risk management solutions.</li><li>Communicate technical results to non-technical stakeholders, ensuring transparency and clarity.</li></ul> Required Skills:<ul><li>Technical Expertise:</li><li>Proficiency in Python for data analysis, modeling, and automation.</li><li>Strong knowledge of Azure (data storage, processing services) and SQL databases for data management.</li><li>Experience with data modeling, including building and deploying predictive models.</li><li>Analytical & Problem-Solving Skills:</li><li>Ability to interpret large datasets and transform them into actionable investment insights.</li><li>Strong understanding of fixed income markets and credit instruments.</li></ul> Preferred Qualifications:<ul><li>Bachelor’s or Master’s in Data Science, Computer Science, Finance, or a related field.</li><li>Experience in real estate, fixed income or private credit investing is a plus.</li></ul> Please note: This position is not open to 3rd party c2c agencies. No visa sponsorship provided. All applicants must have permanent US work authorization and not require sponsorship now or in the future. Locals/ daily commuting distance only please; no remote or relocation.

<ul><li>4-6 years of work experience with a bachelor’s degree or 3+ years of work experience with an Advanced degree (e.g., MTech, MSc, MBA)</li><li>(Preferred) master’s degree in Statistics, Operations Research, Applied Mathematics, Economics, Data Science, Business Analytics, Computer Science, Marketing Research.</li><li>4-6 years of experience in data-based decision-making, quantitative analysis, & experience applying data science to solve problems such as new customer acquisition, attrition management and product mix models.</li><li>(Mandatory) Expertise in the following activities: Large scale data mining, data cleansing, diagnostics, preparation for Modeling. Predictive modeling and machine learning. Multivariate techniques & predictive modeling – cluster analysis, discriminant analysis, CHAID, logistic & multiple regression analysis. Building data analytics models using Python, ML libraries, Power BI Jupyter/Anaconda. Exploring data & writing analytics algorithms in Python.</li><li>(Preferred) Working knowledge of MS Azure Suite - Azure ML Studio, Azure Data Factory,</li><li>Experience leading other data scientists in machine learning projects.</li><li>Strong verbal, writing & presentation skills.</li><li>Experienced in handling multi-national projects and team engagements.</li></ul>(Preferred) Application of data analytics to manufacturing industries or chemical industries.

About NeudesicPassion for technology drives us, but it’s innovation that defines us. From design to development and support to management, Neudesic offers decades of experience, proven frameworks and a disciplined approach to quickly deliver reliable, quality solutions that help our customers go to market faster. What sets us apart from the rest, is an amazing collection of people who live and lead with our core values. We believe that everyone should be Passionate about what they do, Disciplined to the core, Innovative by nature, committed to a Team and conduct themselves with Integrity. If these attributes mean something to you - we'd like to hear from you. Role SummaryNeudesic is currently seeking a Senior Data Scientist for our Data & AI Practice. This role requires the perfect mix of being a brilliant technologist and also a deep appreciation for how technology drives business value. You will have broad and deep technology knowledge and the ability to architect solutions by mapping client business problems to end-to-end technology solutions. Demonstrated ability to engage senior level technology decision makers in data management, real-time analytics, predictive analytics and data visualization is a must. To be successful, you must exhibit strong leadership qualities necessary for building trust with clients and our technologists, with the ability to deliver ML/DL projects to successful completion. You will partner with solution architects to drive client success by providing practical guidance based on your years of experience in data management and visualization solutions. You will partner with a diverse sales unit to professionally represent Neudesic experience and ability to drive business results. In addition, you will assist in creating sales assets that clearly communicate our value proposition to technical decision makers. Requirements:<ul><li>At least 3+ years of hands-on mathematical modeling experience in business environment</li><li>Bachelor’s degree in quantitative field like Computer Science, Engineering, Business Analytics, Statistics, Mathematics or related field required. Advanced degree is a strong plus</li><li>Experience with Databricks is required</li><li>Experience in R/Python and SQL</li><li>Knowledge of statistical, data mining, machine learning(ML and MLOps), large language model(LLM) and AI techniques (regression, decision trees, clustering, neural networks, and deep learning frameworks, etc.)</li><li>Strong SQL skills and proven experience in working with large datasets and relational databases</li></ul> Preferred Qualifications<ul><li>Experience in Hadoop, Spark, and cloud platform experience</li><li>Experience in working with big data tools/environment, e.g. Hadoop Ecosystem (write complex HQL query, automate production pipeline, etc.), Spark, is a strong plus</li><li>Experience with data visual analysis and BI tools like Tableau and Power BI</li><li>Proven experience in working with cloud computing platforms particularly Azure is a strong plus</li><li>Distinctive communications skills and ability to communicate analytical and technical content in an easy-to-understand way</li><li>Ability to tell stories and make recommendations with data exploratory/visual analysis</li><li>Intellectual curiosity, along with excellent problem-solving and quantitative skills, ability to disaggregate issues, identify root causes and recommend solutions</li><li>Result-driven achievers and proven leaders with the ability to inspire others, build strong relationships, and create a true followership</li><li>Strong people skills, team-orientation, and a professional attitude</li></ul> More about our Predictive Enterprise Service Line:The digital business uses data as a competitive differentiator. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in business understanding and customer engagement. The availability of massive amounts of information, massive computing power and advancements in artificial intelligence allow the digital business to more accurately predict, plan for and capture opportunity unlike ever before. The predictive enterprise service line the evolution from using data strictly as a reporting mechanism of what’s happened to leveraging the latest in advanced analytics to predict and prescribe future business action. Our services include:· Data Management Solutions: We build architectures, policies, practices and procedures that manage the full data lifecycle of an enterprise. We bring internal and exogenous datasets together to formulate new perspectives and drive to data-thinking.· Self-Service Data Solutions: We create classic self-service and modern data-blending solutions that enable end-users to enrich pre-authored analytic reports by blending them with additional data sources.· Real-Time Analytic Solutions: We build real-time analytics solutions on data-in-motion that eliminate the dependency on stale and static data sets resulting in the ability to immediately query and analyze diverse data sets.· Machine Learning Solutions: We build machine-learning solutions that support the most complex decision support systems Neudesic also offers professional development and training for our Consultants. This includes opportunities to gain new technical certifications, develop professionally and grow within the company. Accommodations currently remain in effect for Neudesic employees to work remotely, provided that remote work is consistent with the work patterns and requirements of their team’s management and client obligations. Subject to business needs, employees may be required to perform work or attend meetings on-site at a client or Neudesic location. Phishing Scam NoticePlease be aware of phishing scams involving fraudulent career recruiting and fictitious job postings; visit our <a>Phishing Scams</a> page to learn more. Neudesic is an Equal Opportunity EmployerAll employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Neudesic is an IBM subsidiary which has been acquired by IBM and will be integrated into the IBM organization. Neudesic will be the hiring entity. By proceeding with this application, you understand that Neudesic will share your personal information with other IBM companies involved in your recruitment process, wherever these are located. More Information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here: https://www.ibm.com/us-en/privacy?lnk=flg-priv-usen

About Neudesic:Passion for technology drives us, but it’s innovation that defines us. From design to development and support to management, Neudesic offers decades of experience, proven frameworks and a disciplined approach to quickly deliver reliable, quality solutions that help our customers go to market faster. What sets us apart from the rest, is an amazing collection of people who live and lead with our core values. We believe that everyone should be Passionate about what they do, Disciplined to the core, Innovative by nature, committed to a Team and conduct themselves with Integrity. If these attributes mean something to you - we'd like to hear from you. Role Summary:Neudesic is currently seeking a Senior Data Scientist for our Data & AI Practice. This role requires the perfect mix of being a brilliant technologist and also a deep appreciation for how technology drives business value. You will have broad and deep technology knowledge and the ability to architect solutions by mapping client business problems to end-to-end technology solutions. Demonstrated ability to engage senior level technology decision makers in data management, real-time analytics, predictive analytics and data visualization is a must. To be successful, you must exhibit strong leadership qualities necessary for building trust with clients and our technologists, with the ability to deliver ML/DL projects to successful completion. You will partner with solution architects to drive client success by providing practical guidance based on your years of experience in data management and visualization solutions. You will partner with a diverse sales unit to professionally represent Neudesic experience and ability to drive business results. In addition, you will assist in creating sales assets that clearly communicate our value proposition to technical decision makers. Requirements:<ul><li>At least 3+ years of hands-on mathematical modeling experience in business environment</li><li>Bachelor’s degree in quantitative field like Computer Science, Engineering, Business Analytics, Statistics, Mathematics or related field required. Advanced degree is a strong plus</li><li>Experience with Databricks is required</li><li>Experience in R/Python and SQL</li><li>Knowledge of statistical, data mining, machine learning(ML and MLOps), large language model(LLM) and AI techniques (regression, decision trees, clustering, neural networks, and deep learning frameworks, etc.)</li><li>Strong SQL skills and proven experience in working with large datasets and relational databases</li></ul> Preferred Qualifications:<ul><li>Experience in Hadoop, Spark, and cloud platform experience</li><li>Experience in working with big data tools/environment, e.g. Hadoop Ecosystem (write complex HQL query, automate production pipeline, etc.), Spark, is a strong plus</li><li>Experience with data visual analysis and BI tools like Tableau and Power BI</li><li>Proven experience in working with cloud computing platforms particularly Azure is a strong plus</li><li>Distinctive communications skills and ability to communicate analytical and technical content in an easy-to-understand way</li><li>Ability to tell stories and make recommendations with data exploratory/visual analysis</li><li>Intellectual curiosity, along with excellent problem-solving and quantitative skills, ability to disaggregate issues, identify root causes and recommend solutions</li><li>Result-driven achievers and proven leaders with the ability to inspire others, build strong relationships, and create a true followership</li><li>Strong people skills, team-orientation, and a professional attitude</li></ul> More about our Predictive Enterprise Service Line:The digital business uses data as a competitive differentiator. The explosion of big data, machine learning and cloud computing power creates an opportunity to make a quantum leap forward in business understanding and customer engagement. The availability of massive amounts of information, massive computing power and advancements in artificial intelligence allow the digital business to more accurately predict, plan for and capture opportunity unlike ever before. The predictive enterprise service line the evolution from using data strictly as a reporting mechanism of what’s happened to leveraging the latest in advanced analytics to predict and prescribe future business action. Our services include: <ul><li>Data Management Solutions: We build architectures, policies, practices and procedures that manage the full data lifecycle of an enterprise. We bring internal and exogenous datasets together to formulate new perspectives and drive to data-thinking.</li><li>Self-Service Data Solutions: We create classic self-service and modern data-blending solutions that enable end-users to enrich pre-authored analytic reports by blending them with additional data sources.</li><li>Real-Time Analytic Solutions: We build real-time analytics solutions on data-in-motion that eliminate the dependency on stale and static data sets resulting in the ability to immediately query and analyze diverse data sets.</li><li>Machine Learning Solutions: We build machine-learning solutions that support the most complex decision support systems</li></ul> Neudesic also offers professional development and training for our Consultants. This includes opportunities to gain new technical certifications, develop professionally and grow within the company. Accommodations currently remain in effect for Neudesic employees to work remotely, provided that remote work is consistent with the work patterns and requirements of their team’s management and client obligations. Subject to business needs, employees may be required to perform work or attend meetings on-site at a client or Neudesic location. Phishing Scam Notice:Please be aware of phishing scams involving fraudulent career recruiting and fictitious job postings; visit our <a>Phishing Scams</a> page to learn more. Neudesic is an Equal Opportunity Employer:All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law. Neudesic is an IBM subsidiary which has been acquired by IBM and will be integrated into the IBM organization. Neudesic will be the hiring entity. By proceeding with this application, you understand that Neudesic will share your personal information with other IBM companies involved in your recruitment process, wherever these are located. More Information on how IBM protects your personal information, including the safeguards in case of cross-border data transfer, are available here: https://www.ibm.com/us-en/privacy?lnk=flg-priv-usen

Data ScientistIrving, Texas6+ Months Primary SkillsHypothesis Testing, T-Test, Z-Test, Regression (Linear, Logistic), Python/PySpark, SAS/SPSS, Statistical analysis and computing, Probabilistic Graph Models, Great Expectation, Evidently AI, Forecasting (Exponential Smoothing, ARIMA, ARIMAX), Tools(KubeFlow, BentoML), Classification (Decision Trees, SVM), ML Frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet), Distance (Hamming Distance, Euclidean Distance, Manhattan Distance), R/ R StudioSpecializationData Science Advanced: Senior Data ScientistJob requirementsWhat you’ll be doing... This candidate will perform analytics, create predictive models, apply machine learning techniques, and/or develop GenAI methods for high-visibility projects, as a member of a collaborative and open team that prides themselves on innovative solutions.The data scientist will explore information from multiple sources in order to gain maximum insight and provide a competitive advantage.The “data science” tasks may include statistical analyses, knowledge discovery, data mining, machine learning, and predictive modeling.Responsibilities will include: -Performing data studies of new and diverse data sources. - Conducting statistical modeling and experiment design.Discovering “stories” told by the data and present them to peers, software developers, business analysts and business managers.Creating and validating predictive models and advanced algorithms; train AI and machine learning algorithms.What are we looking for: You’ll need to have:Bachelor's degree or four or more years of work experience. - Six or more years of analytics and data science experience.Strong knowledge of programming and pattern recognition.Mastery of statistics, machine learning, algorithms, predictive modeling, and advanced mathematics.Knowledge of deep learning and GenAI techniques.Experience working with security data.Experience working with networking data.Experience using SQL (Structured Query Language) and other programming languages (R, C, Python) for statistical computing, graphics, and data mining.Experience with RDBMS, columnar, and NoSQL database technologies.Experience with Big Data and related tools such as Hadoop or Spark .Familiarity with tools such as R, Rstudio, Python scipy and numpy, Jupyter notebook is desired.Even better if you have one or more of the following:Advanced Degree in one of: Computer Science, Data Science, Physics (or other science), Engineering, or Mathematics/StatisticsStrong critical thinking skills and the ability to relate them to Verizon business processes and operations.Excellent verbal and written communication skills as well as the ability to bridge the gap between data science and business management.Ability to collaborate with business units, IT, and data scientists across the enterprise to support descriptive and predictive analytics processes. -Strong exploratory analysis skills and ability to think and research creatively.

We are seeking an individual to work with a Fortune 50 Broadcast Media & Entertainment leader located in New York, New York. As the Experimentation Manager, you will be directly responsible for being the experimentation leader for Advertisements. In this role, you will have the opportunity to partner with Ads, product, engineering, and other experts to shape a shared experimentation playbook to enable trustworthy personalization and visualizations for consumers. Minimum Qualifications:<ul><li>4+ years of applied experience in Ads experimentation at an eCommerce, social network, direct-to-consumer, media entertainment company or similar tech company</li><li>BA/BS in technical or quantitative discipline or significant work experience</li><li>Experience with experiment design and platforms (i.e., in house built, Optimizely, split.io, etc.)</li><li>Extensive knowledge of statistics and analytical concepts</li><li>Coding skills for analytics and data analysis (Python, R, SQL)</li><li>Experience in using data to drive product decisions and change opinions</li><li>Direct experience working with a diverse set of stakeholders</li><li>Utilize excellent communication skills to clearly distill the essence of your technical work to audiences of all levels and across multiple functional areas</li></ul> Responsibilities:<ul><li>Work with Ads, Product, Decision Science, UX and Engineering to lay out a comprehensive experimentation playbook and roadmap</li><li>Manage an experimentation platform roadmap that supports stakeholder goals and advanced the experimentation practice</li><li>Develop an end-to-end experimentation process that is deeply integrated with Ads, product, and engineering development lifecycle</li><li>Translate insights into Ads and product strategy to empower execution in a data-informed manner</li><li>Deeply understand the ecosystem, defining and analyzing metrics that evaluate the trajectory and inform the success of products</li><li>Communicate insights, vision and strategy with executive leadership and key stakeholders</li><li>Present research on statistics, experimentation, revenue impact, ads impact, user behavior, product enhancements, and metrics development/methodology of all levels of the company ensuring transparency and partnership</li><li>Foster a culture of execution excellence and analytical rigor</li></ul> What’s in it for you?<ul><li>Working for a well-known, globally leading Media Streaming organization</li><li>Exposure to high-level business professionals in a variety of departments and geographic locations</li><li>Opportunity to work and grow your career in fast-paced environment</li></ul>

BettingJobs are currently recruiting for a Senior NBA Data Scientist based in London for an innovative betting company. Responsibilities:<ul><li>Lead the development of models and supervise ad hoc analysis using a variety of data sources to solve tasks relevant to the business (e.g. supporting development of existing and/or new sports forecasting products)</li><li>Extract meaningful insight from sports data using sound Mathematical/Statistical principles</li><li>Collaborate with and lead other members of the Data Science team to propose ideas and solve modelling problems relating to new/existing products</li><li>Follow typical development processes in terms of code management and structure</li><li>Liaise with various teams around the business (including Model Engineering and Data Collection teams where appropriate) to assist with tasks relevant to the modelling team</li></ul> Requirements:<ul><li>5+ years’ experience in sports betting/analytics industry in a quantitative or data science role</li><li>Possesses significant experience and a passion for statistical modelling of MLB or NBA</li><li>Advanced knowledge of statistical modelling and machine learning, with relevant experience in the use of relevant Python libraries e.g. scikit-learn, xgboost, tensorflow, pymc3, statsmodels (and R equivalents)</li><li>Experience generating reports, dashboards and data visualisations to explain the results and behaviour of models</li><li>Experience with concurrent development source control (GIT)</li><li>Familiarity with SQL and experience working with relational databases</li><li>Excellent presentation, documentation, time management, communication skills with the ability to work collaboratively and autonomously</li><li>Strong problem-solving skills with a pragmatic and analytical outlook</li></ul>

Himss Data Scientist Interview Guide

Overview

Himss Data Scientist Salary

Himss Data Scientist Interview Process

Himss Data Scientist Interview Questions

Himss Data Scientist Jobs