Entytle - Data Scientist - Python

Entytle is seeking a highly motivated and talented Data Scientist - Python to join our team. As an entry-level data scientist, you will play a crucial role in driving business growth by extracting insights from complex data sets and developing predictive models to inform business decisions.

As a Data Scientist - Python at Entytle, you will work closely with cross-functional teams to design, develop, and deploy data-driven solutions that drive business outcomes. Your primary focus will be on analyzing large data sets, identifying trends, and building machine learning models using Python to solve real-world problems.

The ideal candidate will have a strong foundation in data science, statistics, and computer science, with a passion for working with data to tell compelling stories. You will be expected to have a solid understanding of data structures, algorithms, and data visualization techniques, as well as experience working with Python libraries such as Pandas, NumPy, and Scikit-learn.

Responsibilities:

• Collect, analyze, and interpret large data sets to identify trends and insights
• Develop and deploy machine learning models using Python to solve business problems
• Collaborate with cross-functional teams to design and implement data-driven solutions
• Work with data visualization tools such as Matplotlib and Seaborn to create interactive and informative dashboards
• Develop and maintain data quality and data integrity across various data sources
• Stay up-to-date with industry trends and emerging technologies in data science and machine learning

Requirements:

• Bachelor's degree in Computer Science, Statistics, Mathematics, or related field
• 0-2 years of experience in data science or related field
• Strong programming skills in Python, with experience working with Pandas, NumPy, and Scikit-learn
• Solid understanding of data structures, algorithms, and data visualization techniques
• Experience working with data visualization tools such as Matplotlib and Seaborn
• Strong analytical and problem-solving skills, with attention to detail and ability to work in a fast-paced environment
• Excellent communication and collaboration skills, with ability to work effectively with cross-functional teams

Nice to Have:

• Experience working with big data technologies such as Hadoop, Spark, and NoSQL databases
• Familiarity with cloud-based data platforms such as AWS, Google Cloud, or Azure
• Experience with deep learning frameworks such as TensorFlow or Keras
• Knowledge of data engineering principles and practices

What We Offer:

• Opportunity to work with a talented team of data scientists and engineers on complex and challenging problems
• Collaborative and dynamic work environment with a strong focus on innovation and learning
• Professional development opportunities, including training and education programs
• Flexible work arrangements, including remote work options
• Access to cutting-edge technologies and tools, including Python, R, and SQL

Location: Our office is located in a vibrant and diverse neighborhood, with easy access to public transportation and a range of amenities. If you're excited about working in data science and are looking for a challenging and rewarding role, we'd love to hear from you.

As a Data Scientist - Python at Entytle, you will have the opportunity to work on complex and challenging problems, collaborate with talented teams, and drive business growth through data-driven insights. If you're passionate about data science and are looking for a role that will challenge and engage you, we encourage you to explore this opportunity further.

• Education
  • Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, Physics, or Engineering
  • Relevant coursework in Data Structures, Algorithms, Computer Systems, and Software Engineering
• Technical Skills
  • Proficiency in Python programming language
  • Experience with popular Python libraries and frameworks such as NumPy, pandas, scikit-learn, TensorFlow, and Keras
  • Familiarity with data visualization tools like Matplotlib and Seaborn
  • Knowledge of SQL and experience with database management systems
  • Understanding of cloud-based technologies and platforms, such as AWS or Google Cloud
• Data Science Skills
  • Strong understanding of machine learning concepts, including supervised and unsupervised learning, regression, classification, clustering, and neural networks
  • Experience with data preprocessing, feature engineering, and model evaluation
  • Familiarity with deep learning architectures and techniques, such as CNNs and RNNs
  • Knowledge of statistical modeling and hypothesis testing
• Data Analysis and Problem-Solving
  • Ability to collect, analyze, and interpret large data sets
  • Strong problem-solving skills, with the ability to break down complex problems into manageable components
  • Experience with data storytelling and communicating insights to non-technical stakeholders
• Collaboration and Communication
  • Ability to work effectively in a team environment, collaborating with cross-functional teams, including engineering, product, and business stakeholders
  • Strong communication skills, with the ability to present complex technical information to non-technical audiences
  • Experience with version control systems, such as Git, and collaborative development tools, such as Jupyter Notebooks
• Business Acumen
  • Understanding of business operations and the ability to identify opportunities for data-driven insights to drive business growth
  • Familiarity with industry trends and emerging technologies, such as AI and machine learning
• Analytical and Critical Thinking
  • Strong analytical and critical thinking skills, with the ability to evaluate complex data sets and identify patterns and trends
  • Ability to think creatively and develop innovative solutions to complex problems
• Adaptability and Flexibility
  • Willingness to learn and adapt to new technologies, tools, and methodologies
  • Ability to work in a fast-paced environment, with the ability to prioritize tasks and manage multiple projects simultaneously
• Location Specific Requirements
  • Ability to work from the Maharashtra location, with occasional meetings and collaborations with team members
• Soft Skills
  • Strong time management and organizational skills, with the ability to meet deadlines and deliver high-quality results
  • Ability to work independently, with minimal supervision, and as part of a team
  • Strong interpersonal skills, with the ability to build strong relationships with colleagues and stakeholders
• Nice to Have
  • Experience with big data processing frameworks, such as Hadoop or Spark
  • Familiarity with containerization tools, such as Docker
  • Knowledge of agile development methodologies and experience with project management tools, such as Jira or Asana
  • Participation in data science competitions or contribution to open-source projects
  • Certification in data science or a related field, such as Certified Data Scientist or Certified Analytics Professional

• Develop and implement machine learning models using Python and relevant libraries such as scikit-learn, TensorFlow, and PyTorch to drive business growth and improve data-driven decision-making at Entytle. • Work closely with cross-functional teams, including data engineering, product, and business stakeholders to identify key business problems and develop data-driven solutions that meet the needs of Entytle's clients. • Collect, process, and analyze large datasets from various sources, including databases, APIs, and files, to gain insights and inform business decisions, ensuring data quality and integrity. • Design, develop, and maintain complex data pipelines and architectures to support the development of machine learning models and other data-driven applications, leveraging tools like Apache Beam, AWS Glue, or similar technologies. • Perform exploratory data analysis to identify trends, patterns, and correlations, and communicate findings to both technical and non-technical stakeholders through clear and concise reports and visualizations using tools like Matplotlib, Seaborn, or Plotly. • Collaborate with the data engineering team to develop and maintain scalable data infrastructure, ensuring seamless data flow and integration with various data sources and systems, including relational databases, NoSQL databases, and cloud storage services. • Stay up-to-date with industry trends and emerging technologies in the field of data science, including deep learning, natural language processing, and computer vision, and apply this knowledge to drive innovation and improvement in Entytle's data science capabilities. • Develop and maintain technical documentation of data science projects, including data pipelines, models, and results, to ensure transparency, reproducibility, and knowledge sharing across the team. • Work with the product team to integrate data-driven insights into product development, ensuring that products are informed by data-driven decision-making and meet the needs of Entytle's clients. • Participate in code reviews, ensuring that code is maintainable, efficient, and follows best practices, and contribute to the development of the team's coding standards and guidelines. • Develop and maintain dashboards and reports to track key performance metrics, using tools like Tableau, Power BI, or D3.js, to provide insights and inform business decisions. • Collaborate with stakeholders to identify opportunities for process improvement and automation, leveraging data science and machine learning to drive efficiency and reduce costs. • Participate in the development of Entytle's data science roadmap, identifying areas for growth and investment, and contributing to the development of the company's data-driven strategy. • Work in an Agile environment, collaborating with cross-functional teams, and adapting to changing priorities and requirements, with a focus on delivering high-quality results in a fast-paced, dynamic environment. • Develop and maintain a strong understanding of Entytle's business operations, including the company's products, services, and target markets, to inform data-driven decision-making and drive business growth. • Leverage Python and relevant libraries to develop and deploy data-driven applications, including data wrangling, feature engineering, and model development, with a focus on delivering high-quality, scalable, and maintainable code. • Work with large datasets, including data preprocessing, data cleaning, and data transformation, to prepare data for modeling and analysis, using tools like Pandas, NumPy, and data manipulation libraries. • Utilize data visualization tools to communicate insights and results to stakeholders, including the development of interactive dashboards and reports, and the creation of data-driven stories to inform business decisions. • Stay current with advancements in data science and machine learning, including new techniques, tools, and methodologies, and apply this knowledge to drive innovation and improvement in Entytle's data science capabilities, with a focus on delivering business value and driving growth.

Entytle - Data Scientist - Python Selection Process

Overview of the Selection Process: The selection process for the Data Scientist - Python role at Entytle is designed to assess a candidate's technical skills, data analysis abilities, and behavioral competencies. The process consists of multiple rounds, each evaluating a specific aspect of the candidate.

Round 1: Online Technical Assessment

• The online technical assessment is a 60-minute test that evaluates a candidate's Python programming skills, data structures, and algorithms.
• The test consists of 20-25 questions, including:
  • Python syntax and data structures (lists, dictionaries, etc.)
  • Data analysis and manipulation using popular libraries (Pandas, NumPy, etc.)
  • Basic machine learning concepts and algorithms
• The test is hosted on a platform that provides a simulated environment for coding and testing.

Round 2: Data Analysis and Case Study

• Candidates who clear the online technical assessment are invited to a data analysis and case study round.
• This round assesses a candidate's ability to analyze complex data sets, identify patterns, and draw meaningful insights.
• The case study is based on a real-world scenario, and candidates are provided with a dataset and a set of questions to answer.
• The evaluation criteria include:
  • Data analysis and interpretation skills
  • Ability to communicate insights effectively
  • Understanding of data visualization techniques

Round 3: Technical Interview

• The technical interview is a 45-minute to 1-hour session with a senior data scientist or a technical lead.
• The interview focuses on:
  • Advanced Python concepts (decorators, generators, etc.)
  • Machine learning algorithms and techniques (supervised, unsupervised, etc.)
  • Data modeling and evaluation metrics
• The interviewer may also ask behavioral questions to assess a candidate's:
  • Problem-solving skills
  • Collaboration and teamwork experience
  • Adaptability and willingness to learn

Round 4: Behavioral Interview

• The behavioral interview is a 30-minute to 45-minute session with a member of the HR team or a senior manager.
• The interview focuses on assessing a candidate's:
  • Past experiences and accomplishments
  • Behavioral competencies (communication, teamwork, etc.)
  • Career goals and motivations
• The interviewer may ask scenario-based questions to evaluate a candidate's:
  • Conflict resolution and negotiation skills
  • Time management and prioritization abilities
  • Leadership and initiative-taking

Round 5: Final Interview and Offer

• The final interview is a 30-minute to 45-minute session with a senior leader or a member of the executive team.
• The interview focuses on:
  • Overall fit for the company culture
  • Alignment with company values and mission
  • Expectations and goals for the role
• Candidates who clear the final interview are extended an offer, which includes:
  • Salary and benefits package
  • Details of the role and responsibilities
  • Information about the team and company culture

Tips for Preparation:

• Review Python fundamentals, data structures, and algorithms.
• Practice data analysis and machine learning concepts using popular libraries (Pandas, Scikit-learn, etc.).
• Develop a strong understanding of data visualization techniques and tools (Matplotlib, Seaborn, etc.).
• Prepare to answer behavioral questions using the STAR method ( Situation, Task, Action, Result).
• Research the company culture, values, and mission.
• Practice whiteboarding exercises to improve problem-solving and communication skills.

Key Skills and Qualities:

• Strong Python programming skills
• Experience with data analysis and machine learning libraries
• Excellent communication and collaboration skills
• Ability to work with complex data sets and identify patterns
• Strong problem-solving skills and adaptability
• Alignment with company values and mission

Evaluation Criteria:

• Technical skills and expertise
• Data analysis and interpretation abilities
• Communication and collaboration skills
• Behavioral competencies (teamwork, leadership, etc.)
• Cultural fit and alignment with company values

Company Overview

• Entytle is a technology-driven company that specializes in providing innovative solutions to businesses.
• The company is headquartered in Maharashtra, India, and has established itself as a leading player in the industry.

Work Culture

• Entytle fosters a collaborative and dynamic work environment that encourages creativity, innovation, and growth.
• The company values diversity and inclusion, and strives to create a workplace that is welcoming and respectful to all employees.
• Employees at Entytle are encouraged to take ownership of their work and are given the autonomy to make decisions that impact their projects.

Values and Mission

• Entytle's mission is to empower businesses through technology, and to make a positive impact on the communities it serves.
• The company's core values include:
  • Innovation: Encouraging creativity and innovation in all aspects of the business.
  • Customer-centricity: Focusing on delivering exceptional customer experiences.
  • Integrity: Conducting business with honesty, transparency, and ethics.
  • Teamwork: Collaborating and working together to achieve common goals.

Employee Benefits

• Entytle offers a comprehensive benefits package that includes:
  • Competitive salary and bonuses
  • Health insurance and wellness programs
  • Retirement savings plan
  • Paid time off and holidays
  • Opportunities for professional growth and development
• The company also provides a range of perks, including:
  • Flexible working hours
  • Remote work options
  • Access to cutting-edge technology and tools
  • On-site fitness classes and recreational activities

Career Growth and Development

• Entytle is committed to helping its employees grow and develop their skills.
• The company provides:
  • Training and development programs
  • Mentorship opportunities
  • Cross-functional learning and exposure
  • Opportunities for career advancement
• Employees at Entytle are encouraged to take ownership of their career goals and are supported by their managers and peers.

Diversity, Equity, and Inclusion

• Entytle values diversity and is committed to creating an inclusive workplace.
• The company:
  • Celebrates different cultures and backgrounds
  • Promotes equal opportunities for all employees
  • Provides resources and support for underrepresented groups
  • Encourages open and honest communication

Work-Life Balance

• Entytle recognizes the importance of work-life balance and encourages employees to prioritize their well-being.
• The company:
  • Offers flexible working hours
  • Provides paid time off and holidays
  • Encourages employees to take breaks and recharge
  • Supports employee wellness programs

Technology and Infrastructure

• Entytle is a technology-driven company and invests heavily in its infrastructure.
• The company:
  • Uses cutting-edge technology and tools
  • Provides access to state-of-the-art equipment and software
  • Encourages innovation and experimentation
  • Has a robust IT infrastructure to support business operations

Leadership and Management

• Entytle's leadership team is comprised of experienced professionals who are passionate about technology and innovation.
• The company's management style:
  • Encourages collaboration and teamwork
  • Fosters a culture of transparency and openness
  • Supports employee growth and development
  • Makes data-driven decisions

Social Responsibility

• Entytle is committed to making a positive impact on the community.
• The company:
  • Supports local charities and initiatives
  • Encourages employee volunteerism
  • Invests in sustainable practices and environmental initiatives
  • Partners with organizations to drive positive change

Recognition and Awards

• Entytle has received recognition and awards for its innovative solutions and commitment to excellence.
• The company:
  • Has been featured in industry publications and media outlets
  • Has received awards for its technology and innovation
  • Has been recognized for its commitment to diversity and inclusion

Employee Testimonials

• Employees at Entytle are proud to work for the company and have shared their positive experiences:
  • "Entytle has provided me with opportunities to grow and develop my skills. The company culture is collaborative and supportive, and I feel valued and respected." - Software Engineer
  • "I've been impressed by the company's commitment to innovation and customer-centricity. The team is passionate and driven, and it's exciting to be a part of." - Product Manager