Data Scientist

3 months ago

bangalore, India Hiret Consulting Full time

Job Title: Data Scientist


Years of Experience: 2 - 5 years


Educational Qualifications:

B.Tech/B.E/M.E/M.Tech/MSC in Data Science/Computer Science/Statistics/AI/ML or Minimum 2 years professional experience in the field of data science, ML or business intelligence.

2+ years of experience in building and deployment of machine learning models.


Skills Required:

Demonstrated passion for data science and a strong desire to pursue a career in this field.

Experience in extracting and processing large files/data sets.

Experience interpreting model results and translating insights into business recommendations.

Prior experience in application domains such as Manufacturing/Automotive, e-commerce, fintech, Data Science Services, etc., involving agile working practices.


Location: Kudlugate, Bangalore

Position Type: Full Time

Role Type: Individual Contributor


Role Summary / Profile Summary:

We are seeking an experienced and highly skilled Data Scientist to join our team. As a Data Scientist, you will be responsible for development and implementation of data-driven solutions. You will collaborate with cross-functional teams to identify business problems, design analytical approaches, and provide actionable insights.


Roles and Responsibilities:

  • Design and implement advanced data analysis techniques to extract meaningful insights from complex and large datasets.
  • Develop and deploy machine learning models to solve business problems and optimize processes.
  • Assess the effectiveness and accuracy of new data sources and data gathering techniques.
  • Propose solutions and strategies to business challenges. Apply domain knowledge to understand business requirements and provide relevant solutions.
  • Analyze large amounts of information to discover trends and patterns.
  • Create data visualizations and reports to effectively communicate findings and recommendations to stakeholders.
  • Ability to understand business concerns and formulate them as technical problems that can be solved using data and ML.
  • Collaborate with cross-functional teams to identify opportunities for data-driven decision-making and develop strategies to leverage data assets.
  • Stay updated with the latest advancements in data science, machine learning, and big data technologies to drive innovation within the organization.


Soft Skills Required:

  • Excellent written & Verbal Communication skills to collaborate with cross-functional teams and describe findings to a technical and non-technical audience.
  • Have a proactive communication and able to challenge existing approach and recommend new advanced machine learning techniques.
  • Participate in business diagnostic, problem definition, solution proposal, project design, and resource planning. Independently lead analytical projects to completion, collaborate with stakeholders and utilize excellent communication skills to gain consensus on the recommendation.
  • Ability to multitask and meet deadlines in a fast-paced environment.
  • Self-motivated, detail-oriented, and proactive in identifying opportunities for improvements.
  • Good Presentation skills to communicate findings and recommendations to Management and stakeholders.
  • Ability to work independently and as part of a team.
  • Strong Problem Solving and Analytical Skills.
  • Strong Analytical Skills to interpret data, generate insights and make data driven decisions.


Technical Skills Required:

  • Strong grasp of Statistics, Mathematical concepts, and algorithms.
  • Experience using statistical computer languages (R, Python, SQL, etc.) to manipulate data and draw insights from large data sets. Familiarity with Scala and Java would be an asset.
  • Experience with Python libraries such as Pandas, NumPy, SciPy, Scikit-Learn
  • Experience in programming, knowledge of OOPS principles, knowledge of design patterns and Java.
  • Experience with variety of machine learning techniques (logistic regression, linear regression, lasso regression, k-means, random forest, XG boost, KNN, SVM, clustering, decision tree, and neural networks).
  • Must have deployed multiple ML models.
  • Knowledge of Source Control management tools like GIT, CVS, VSS, Subversion etc.
  • Expertise with Microsoft Office products; including Excel, PowerPoint, Word.
  • Knowledge of Data Structures, relational data, and big data platfoms.
  • Experience using business intelligence tools (e.g., Tableau, Google Data Studio, Power BI) and data frameworks (e.g., Hadoop).
  • Deep understanding of a specific domain (e.g., Automotive, finance, healthcare, e-commerce) and the ability to apply domain knowledge to data analysis.

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