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Data Scientist
4 months ago
Job Title: Data Scientist
Years of Experience: 2 - 5 years
Educational Qualifications:
Required/Minimum Qualifications:
- B.Tech/B.E/M.E/M.Tech/MSC in Data Science/Computer Science/Statistics/AI/ML or Minimum 3 years professional experience in the field of data science, ML or business intelligence.
- 3+ 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: Bangalore
Position Type: Full Time
Role Type: Individual Contributor
Reporting to: CEO
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 leading a team of data scientists and driving the 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:
- Lead a team of associate data scientists and provide guidance and mentorship to ensure successful project delivery.
- Lead and manage projects, ensuring timely delivery and adherence to quality standards.
- 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.
- Demonstrate leadership by providing thought leadership, mentorship, and training to junior data scientists in the department.
- 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.
