Bharti Soft Tech is hiring for a fresher entry level Data Scientist role in India

Position:

• Data Scientist

Company:

• Bharti Soft Tech Pvt. Ltd.

Location:

• Vadodara, Gujarat, India

Job Type:

• Full-Time

Job Mode:

• Onsite

Job Requisition ID:

• Not Specified

Years of Experience:

• Not Specified (but looks like an entry level position)

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Company Description:

• Bharti Soft Tech Pvt. Ltd. is an ISO 9001-2008 certified IT service provider established in 2006. Headquartered in France with offices in Germany and India, Bharti Soft Tech delivers high-end product development and consulting services to a global clientele.
• Specializing in executing turnkey projects, the company operates across various industry verticals, providing multifaceted IT services and solutions. With a global presence, it has worked with esteemed brands such as Orange Business Services, Vodafone, and France Telecom.
• The team at Bharti Soft Tech consists of highly skilled and dynamic professionals who bring global experience and passion to IT-related market segments. Their focus on quality, reliability, and innovation helps the company deliver client-focused solutions using the latest technologies.
• As a client-centric organization, Bharti Soft Tech emphasizes well-conceptualized and executed projects. Their commitment to high-quality services has allowed them to build long-lasting relationships with international brands.

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Profile Overview:

• Job Purpose: The Data Scientist will focus on research, development, and innovation. This includes building strong relationships with clients, acquiring strategic datasets, and offering new, cutting-edge solutions through product prototyping. The role requires balancing multiple projects, identifying potential roadblocks, and delivering high-quality results in a fast-paced environment.

• Key Responsibilities: The Data Scientist will perform data analysis, create innovative algorithms, and apply machine learning and data mining techniques to large datasets. They will develop data-driven models to solve business problems, validate model performance, and present findings to internal and external stakeholders. The role demands independent decision-making and innovation, alongside effective project management and collaboration with cross-functional teams.

• Expectations: The ideal candidate will lead analytical projects, mentor team members, and contribute to knowledge-sharing initiatives. They should be proactive in seeking personal development opportunities and staying updated on advancements in data science technologies and methodologies.

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Qualifications:

• Educational Requirements:

  • Advanced Degree in Machine Learning, Computer Science, Electrical Engineering, Physics, Statistics, Applied Mathematics, or related fields.

• Technical Skills:

  • Expertise in statistical inference, probability, optimization algorithms, linear algebra, and calculus.
  • Strong understanding of analytical methods, including regression analysis, machine learning, and deep learning.
  • Ability to apply key techniques for cross-validation, Bayesian shrinkage, and in-sample vs out-of-sample analysis.
  • Experience in handling large datasets using tools like Hadoop and Spark.
  • Proficiency in programming languages such as Python or C++.

• Technological Expertise:

  • Familiarity with modern technologies for processing large datasets, including Graph databases, time-series databases, and natural language processing tools for unstructured data.

• Communication and Collaboration:

  • Excellent communication skills with the ability to work effectively in cross-functional teams.
  • Domain-specific knowledge of products and services.

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Additional Information:

Data Analysis:

• The primary responsibility of the Data Scientist is to analyze and process large datasets using advanced techniques. This involves:
  • Designing efficient data storage structures.
  • Applying machine learning and data mining techniques to derive actionable insights.
  • Building tools for data processing and retrieval.
  • Developing models to quantify the value of datasets.
  • Conducting return on investment (ROI) analysis and validating model performance.

Problem Solving and Innovation:

• Innovating solutions based on client data, the Data Scientist will:
  • Develop business assumptions and best practices for uncovering insights.
  • Lead efforts to improve client solutions.
  • Participate in knowledge-sharing activities and roundtable discussions.

Project Management:

• The role includes:
  • Managing multiple projects, from input gathering to delivery.
  • Leading projects to ensure the timelines and model fits are optimal.
  • Collaborating with internal and external stakeholders to improve analytical solutions.

Teamwork and Knowledge Sharing:

• As part of the team, the Data Scientist will:
  • Share expertise with peers and mentor junior team members.
  • Advocate for analytics through publications, presentations, and conferences.

Personal Development:

• A critical part of this role includes:
  • Maintaining a personal development plan.
  • Staying connected with industry movements and trends.
  • Actively seeking opportunities to enhance software and analytics knowledge.

Client and Internal Relationship Management:

• Leading client engagements to improve data quality, model fits, and project timelines.
• Actively participating in internal and external presentations and discussions.

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Summary of Responsibilities:

Data Analysis (40%):

• Analyze, process, and document large datasets.
• Apply machine learning and data mining techniques to extract value.
• Design efficient data structures and storage systems.
• Develop models to assess the value of datasets.
• Conduct ROI analysis and validate models.

Problem Solving and Innovation (25%):

• Develop solutions using client data.
• Establish best practices for data usage.
• Lead knowledge-sharing sessions.

Project Management (10%):

• Independently manage projects.
• Collaborate with internal and external teams.
• Influence decisions at the account and project level.

Client and Internal Relationship (10%):

• Manage client relationships.
• Improve analytical solutions.
• Lead team efforts for optimal solutions.

Teamwork and Knowledge Sharing (5%):

• Share expertise and mentor team members.
• Participate in conferences and roundtables.

Personal Development (10%):

• Maintain awareness of industry trends.
• Develop a personal growth plan.
• Seek feedback to enhance skills.

Please click here to apply.

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