Data Specialist Job at Trackmind in Hyderabad – AI & Data Science Role

By Kaabil Jobs

Any Graduate Blog Experienced Jobs Jobs in Hyderabad

data-Specialist-job-in-hyderabad-at-trackmind
  • Share This Job Post

Data Specialist job in Hyderabad AI ML Data Specialist

Trackmind is seeking an experienced Data Specialist for an on-site, full-time role based in Hyderabad, Telangana, India. This position is ideal for professionals with a strong background in data analysis, ETL processes, and Python development. As a Data Specialist at Trackmind, you’ll play a critical role in building predictive models, ensuring data quality, and contributing to innovative AI/ML projects. This is an excellent opportunity for individuals passionate about data and eager to work with a talented, multidisciplinary team.

𝐏𝐚𝐲 𝐀𝐟𝐭𝐞𝐫 𝐏𝐥𝐚𝐜𝐞𝐦𝐞𝐧𝐭 𝐓𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐏𝐫𝐨𝐠𝐫𝐚𝐦- 𝐆𝐞𝐭 𝐏𝐥𝐚𝐜𝐞𝐝 𝐈𝐧 𝐓𝐨𝐩 𝐌𝐍𝐂’

Overview

Job Overview for Freshers at Trackmind

  • Job Position: Data Specialist
  • Job Location: Hyderabad, Telangana
  • Salary Package: As per Company Standards
  • Full/Part Time: Full Time
  • Req ID: NA
  • Education Level:Bachelor’s degree / Any Graduation
  • Company Website: www.trackmind.com
  • Minimum Qualifications:
    • Bachelor’s degree in Computer Science, Data Science, or a related field.
    • Minimum of 3 years of experience in Python development and data analysis.
  • Preferred Qualifications:
    • Proficiency in AI/ML libraries like TensorFlow, PyTorch, and scikit-learn.
    • Strong knowledge of ETL processes, data preprocessing, and analysis.
    • Familiarity with NER (Named Entity Recognition) and knowledge graphs is a plus.

As a Data Specialist at Trackmind, you will be responsible for managing data processes, designing robust predictive models, and maintaining data accuracy and relevance. This role involves collaborating with experts across disciplines to support innovative AI/ML projects, and it is ideal for someone dedicated to continuous learning and exploration in data science.

  • Develop, optimize, and maintain ETL processes to ensure data quality and integrity across systems.
  • Design and implement high-quality predictive systems utilizing AI/ML techniques, including LLM-based applications.
  • Preprocess and analyze data to extract valuable insights, supporting high-quality model performance.
  • Evaluate and fine-tune models using appropriate performance metrics to improve accuracy and effectiveness.
  • Collaborate closely with data scientists, data engineers, and front-end engineers on project requirements and implementations.
  • Stay up-to-date with industry advancements, proactively exploring new methods and technologies relevant to data science.
  • Technical Skills: Proficiency in Python, experience with ETL, AI/ML techniques, LLM-based applications, and predictive model development.
  • Analytical Skills: Ability to analyze data and preprocess it to ensure quality, model relevance, and insight extraction.
  • Collaboration: Strong interpersonal skills to work effectively in a multidisciplinary environment.
  • Continuous Learning: Commitment to staying updated on advancements in data science and machine learning.


Join Trackmind as a Data Specialist and be part of a dynamic team that leverages AI and ML to drive data solutions. This role is ideal for a skilled professional eager to work in Hyderabad on-site, collaborating on cutting-edge data projects. Trackmind offers an enriching environment for career growth in data science and technology, making this position perfect for professionals passionate about data-driven insights and innovation.

This Data Specialist role in Hyderabad offers an on-site, collaborative work environment, providing ample opportunities to engage with a dedicated team in data science and machine learning.

Apply In Below Link

Apply Link:- Click Here To Apply (Apply before the link expires)

Note:– Only shortlisted candidates will receive the call letter for further roundsTop MNC’s Hiring Across India , Upload Your Resume

  • Share This Job Post

To assist with your interview preparation, here are some technical and non-technical questions you may encounter.

  1. How do you approach ETL process optimization?
    Answer: I focus on ensuring data accuracy and integrity through optimized scripts, efficient data handling, and regular checks for data consistency.
  2. Explain how you use Python for data analysis and preprocessing.
    Answer: I utilize Python libraries like Pandas and NumPy to clean and manipulate data, transforming it into usable formats for model training and analysis.
  3. What experience do you have with LLM-based applications?
    Answer: I have built applications using LLMs, ensuring model quality and relevance by training with industry-specific data and continuously testing for improvement.
  4. Describe your experience with AI/ML libraries like TensorFlow and PyTorch.
    Answer: I have worked with TensorFlow and PyTorch for model training, tuning, and deployment, utilizing these libraries for both image and text-based models.
  5. How do you ensure high model performance in predictive systems?
    Answer: I use performance metrics such as accuracy, precision, and recall, iteratively testing and improving model architecture and parameters to achieve optimal results.
  6. What are knowledge graphs, and how do you leverage them?
    Answer: Knowledge graphs structure data as entities and relationships, useful for complex queries, and I use them to enrich data insights and model training.
  7. How do you manage data preprocessing challenges in large datasets?
    Answer: I break down data into manageable segments, using efficient algorithms to clean and structure it, reducing time and computational resources.
  8. What metrics do you consider when evaluating model accuracy?
    Answer: Common metrics include confusion matrix elements (precision, recall), F1 score, and sometimes AUC-ROC curves, depending on model requirements.
  9. How do you stay updated with new AI/ML methods and technologies?
    Answer: I frequently engage with academic journals, attend webinars, and participate in online courses to stay current with AI/ML trends.
  10. Explain how Named Entity Recognition (NER) works and its applications.
    Answer: NER identifies entities in text, categorizing them (e.g., names, dates), which is valuable for organizing unstructured data and enhancing data models.

  1. Why are you interested in joining Trackmind as a Data Specialist?
    Answer: Trackmind’s focus on innovative AI/ML applications aligns with my passion for data science, and I’m eager to contribute to impactful data-driven projects.
  2. Describe a challenging project you worked on and how you overcame it.
    Answer: I once handled a large dataset with missing values and noise; I used advanced imputation techniques and feature engineering to extract quality data.
  3. How do you handle feedback and continuous improvement?
    Answer: I value constructive feedback, using it to improve my methods and maintain high standards in my work.
  4. What do you enjoy most about working in data science?
    Answer: I enjoy transforming raw data into actionable insights, solving problems through data, and witnessing the impact of data-driven decisions.
  5. How do you prioritize tasks in a fast-paced environment?
    Answer: I organize tasks based on project deadlines and importance, using project management tools to track my progress and ensure timely delivery.
  6. What are your career goals in the data field over the next few years?
    Answer: I aim to deepen my expertise in AI/ML and move towards a leadership role in data science, contributing to larger projects and mentoring others.
  7. How would you describe your teamwork skills?
    Answer: I am collaborative and value diverse perspectives, ensuring open communication and alignment with team goals for successful project outcomes.
  8. What is your approach to learning new technologies?
    Answer: I proactively explore resources and practice new technologies, learning efficiently through hands-on application and continuous experimentation.
  9. How do you handle high-pressure situations?
    Answer: I remain calm and focused, breaking down complex tasks into smaller steps and addressing each systematically to reduce stress.
  10. What excites you about this opportunity with Trackmind?
    Answer: Trackmind’s commitment to cutting-edge data projects and a supportive, collaborative work environment excites me, as it offers tremendous growth and learning opportunities.

Leave a Comment