Job Description: [About this role :

In Gartner’s Services Data Science team, we innovate the way our team helps clients receive value, so technology leaders will be able to make smarter decisions in a different way.

We are searching for a talented associate data scientist to join our team. You will have access to the best facilities, technology and expertise within the industry and will work on challenging business problems. This is an excellent opportunity to be part of a new venture, in a start-up environment where you can truly develop your skill set and knowledge and bring impact to the team.

What you’ll do : 

Here is a sample of some initiatives that our associate data scientists work on

Designing and implementing state of the art Large Language Model (LLM) based agents that seamlessly synthesize complex information and initiate important actions in a business workflow. 
Using NLP models and advanced Generative AI techniques to derive actionable insights from unstructured text data, such as call transcripts and emails. Evaluating the performance of the models, continuously optimizing them for better accuracy and relevance
Building various recommendation tools like client interest predictor and personalized content recommenders to drive higher client value delivery
Develop customer churn prediction models that proactively identify at-risk clients, leverage statistical and machine learning techniques to extract actionable insights from client retention data. 
Build tools to process structured and unstructured data
Engineering features and signals to train ML model from diverse data collection
Collaborate with cross-functional teams to integrate data science solutions into existing systems and user workflows, ensuring seamless data accessibility and usability. 

What you’ll need :

BS/MS/PhD in Computer Science or other technology, Math, Physics, Statistics or Economics (focus on Natural Language Processing, Information Retrieval a plus)
1+ years’ experience in data science methodologies as applied to live initiatives or software development
1+ years of experience in python coding and statistical analysis
Working experience in several of the following:
Prompt Engineering and working with LLMs
Machine Learning and statistical techniques
Data mining and recommendation systems
Natural Language Processing and Information Retrieval
Handling large volumes of data
User behavior modeling
What we offer :

A collaborative, positive culture. You’ll work with people who are as enthusiastic, smart and driven as you are. You’ll be managed by the best too. 
Limitless growth and learning opportunities. We offer the excitement of a fast-paced entrepreneurial workplace and the professional growth opportunities of an established global organization. ]                           Resume: [Romit Ghosh
Kolkata, West Bengal, India
(+91) 7596084891 • <PRESIDIO_ANONYMIZED_EMAIL_ADDRESS> • <PRESIDIO_ANONYMIZED_URL>
Summary
M.Sc. in Economics graduate with over a year of experience applying data science methodologies, Python
coding, and statistical analysis to solve complex business problems. Proficient in developing machine learning
models, leveraging statistical techniques for actionable insights, and handling large volumes of data.
Eager to contribute to Gartner’s Services Data Science team by building innovative solutions like customer churn
prediction models and recommendation tools to drive client value.
Professional Experience
Data Analyst Intern Kolkata, India
Tata Steel Jun 2024 – Jul 2024
• Collaborated with cross-functional teams to analyze competitor KPIs, delivering actionable insights
that enhanced competitive strategy and identified 3 key operational improvements.
• Conducted data-driven analysis of inflation and e-commerce trends using Python, informing major economic
policy proposals and demonstrating strong communication skills.
• Engineered data pipelines to process and manipulate large, complex datasets, ensuring data reliability
by 80% for strategic decision-making.
Data Science Projects
Customer Churn Prediction Model Gokhale Institute of Politics and Economics, 2024
• Developed a customer churn prediction model to proactively identify at-risk clients, leveraging machine
learning techniques (Random Forest, Decision Tree) to achieve 95% prediction accuracy.
• Executed feature engineering from client data and developed a robust data cleaning pipeline, boosting model
accuracy by 25% and improving data reliability by 40%.
• Extracted actionable insights from client retention data to inform a targeted retention strategy, projected
to reduce customer churn by 15% based on user behavior modeling.
Bookstore Management System Gokhale Institute of Politics and Economics, 2023
• Designed and built a tool to process structured data using a normalized SQL database, optimizing query
performance for reporting and reducing data retrieval times by 60%.
• Automated order processing with stored procedures, which reduced stockouts by 20% and enhanced order
fulfillment efficiency by 30%.
Education
Master of Science in Economics 2023 – 2025
Gokhale Institute of Politics and Economics, Pune, India
Bachelor of Science in Economics 2020 – 2023
St. Xavier’s College (Autonomous), Kolkata, India
Skills
Programming Python, SQL, PySpark, R, SAS (Basic), Spark (Basic)
Data Science & Analytics Machine Learning, Statistical Techniques (Regression, T-tests), Hypothesis
Testing, Data Mining, Natural Language Processing (NLP), Prompt Engineering & LLMs
Data Tools Tableau, Power BI, MS Excel, Stata, PowerPoint, Hive (Basic)
Soft Skills Analytical Problem-Solving, Cross-Functional Collaboration, Strategic Decision
Support, Attention to Detail]                                                                                                                                Your resume is missing important keywords related to your job title. Consider incorporating the keywords below to enhance your resume’s effectiveness.                                                                                                                                       scikit-learn 

Example: Implemented machine learning algorithms using Scikit-learn for predictive modeling.

8/10

prompt engineering

Example: Engaged in prompt engineering to optimize large language model outputs.

7/10

data visualization

Example: Created data visualizations to effectively communicate insights to stakeholders.

5/10

nltk

Example: Utilized NLTK for text processing and natural language understanding.

5/10

business intelligence

Example: Utilized business intelligence tools to derive actionable insights from complex datasets.

5/10

strategic decision support

Example: Provided strategic decision support through data-driven analysis and insights.

5/10

data accessibility

Example: Ensured data accessibility for cross-functional teams to facilitate collaboration.

4/10

jupyter

Example: Used Jupyter notebooks for interactive data analysis and model development.

4/10

spacy

Example: Applied SpaCy for natural language processing tasks in data projects.

4/10

hypothesis testing

Example: Performed hypothesis testing to validate data-driven assumptions.

3/10

tensorflow

Example: Built and trained neural networks using TensorFlow for data-driven solutions.

3/10

aws

Example: Deployed machine learning models on AWS for scalable data processing.

3/10

model evaluation

Example: Conducted model evaluation to assess performance and improve accuracy.

3/10

initiative

Example: Demonstrated initiative by leading data science projects to drive business impact.

2/10

critical thinking

Example: Applied critical thinking to solve complex data-related challenges.

2/10                                                                                                              Exact keywords to include in your resume

Importance to your job title

data wrangling

Example: Performed data wrangling to clean and prepare datasets for analysis.

9/10

recommendation systems

Example: Developed recommendation systems to enhance client engagement and value delivery.

9/10

predictive modeling

Example: Implemented predictive modeling techniques to forecast client churn.

8/10

data processing

Example: Engineered data processing pipelines to handle large volumes of data efficiently.

6/10

client retention analysis

Example: Executed client retention analysis to identify at-risk clients and inform strategies.

4/10

Add the right keywords to help your resume pass through applicant tracking systems. Or let us do it for you with our expert resume-writing service.                                                                                                   ATS Compatibility
52%
Recommendations
Stronger resumes typically use only plain text for all headings and content to maximize ATS compatibility. In your document, several headings and skill keywords are bolded or italicized using non-standard LaTeX fonts (e.g., CMR10, CMBX10, CMBX12, SFRM1000, CMCSC10, CMTI10). Consider reformatting your resume in a standard word processor (such as Microsoft Word or Google Docs) using basic system fonts (Arial, Calibri, Times New Roman) and avoiding any special formatting or LaTeX-based styles. This adjustment will help ensure that all sections and keywords are accurately parsed by ATS systems.

We would have expected to see a complete absence of tables or text boxes for optimal ATS parsing. Your resume uses a two-column layout for the Skills section and possibly other areas, which may be implemented as a table or text box in the PDF. To improve ATS compatibility, consider restructuring your resume so that all content flows in a single column from top to bottom without any side-by-side sections, tables, or text boxes.

For best results with ATS software, resumes should use only standard fonts and avoid any unusual characters or symbols. Your document employs several non-standard LaTeX fonts (CMR10, CMBX10, etc.), which may not be recognized by many ATS systems. Rebuilding your resume in a standard format with widely supported fonts like Arial or Calibri will help ensure all your information is read correctly.

Score
Layout and Readability
27%
Recommendations
Stronger resumes typically maintain consistent formatting for section headers, bullet points, and text alignment. In your resume, section headers such as "Summary," "Professional Experience," and "Skills" use different font sizes and styles compared to the rest of the document. Consider standardizing header formatting (font size, boldness, and alignment) across all sections to create a more cohesive and professional appearance.

We would have expected to see uniform font sizes for similar elements throughout your resume. The section headers are noticeably larger than the body text, and there is variation in font size between your name, headers, and content. Using a consistent font size for section headers and another for body text will enhance readability and professionalism.

Consistent formatting of job titles, company names, and employment years helps recruiters quickly scan your experience. In your work experience section, the job title, company name, location, and dates are not formatted uniformly (e.g., alignment of dates varies between sections). Aligning these elements in a consistent manner will improve clarity.                                                           Highlights

You demonstrate strong command of industry-specific terminology throughout your experience and project sections, effectively aligning your skills with the data science and analytics field.

You have presented a clearly defined and well-organized skills section that effectively highlights your key technical and analytical competencies, making it easy for recruiters to assess your fit for data science roles.

You effectively demonstrate adaptability by showcasing experience with diverse projects and responding to evolving business needs, such as analyzing inflation trends and developing new data pipelines.

Score
Soft Skills
59%
Recommendations
While your experience section demonstrates valuable contributions and teamwork, stronger resumes typically include explicit examples of leadership or management responsibilities, such as leading a project, mentoring peers, or managing a small team. For instance, in your Tata Steel internship, you mention collaborating with teams but do not specify any leadership roles. Consider highlighting any instances where you took initiative, coordinated efforts, or guided others to showcase your leadership potential.

Although your resume shows strong technical skills and the ability to extract insights from data, we would have expected to see clear examples of simplifying complex concepts for non-specialist audiences. For example, in your Tata Steel internship or academic projects, you could mention presenting findings to stakeholders without technical backgrounds or translating technical results into actionable business recommendations. Including such details can further demonstrate your communication skills and ability to bridge technical and non-technical domains.                                                               Go through the recomendations and run the resume in latex.