Senior Data Scientist / Principal Data Scientist ; Location: Sunnyvale, CA

Intellisoft Technologies is a leading global information technology firm that specializes in Big Data & AI serving fortune 500 clients for past 21years. Company has been globally recognized for its comprehensive portfolio of services, innovation in technology and strong commitment to sustainability, governed by technocrats with industry experience.
 
At IntelliSoft, our professional development team helps your career by identifying right opportunities and guide you to acquire latest technologies in this fast paced technology world.  We believe in our employees and provide them excellent benefits.
 
****Must have 12+ Years of Experience****

Job Title : Senior Data Scientist / Principal Data Scientist
Location: Sunnyvale, CA

Duration: 6 month, contract to hire

Preferable GC/USC

Required Skills
Python Spark Scala Tensorflow Machine Learning Scikit Torch
 
 

Job Description 
Essential Functions:

An individual must be able to successfully perform the essential functions of this position with or without a reasonable accommodation.
Data Source Identification:
Understand the appropriate data set required to develop simple models by developing initial drafts. Supports the identification of the most suitable source for data. Maintains awareness of data quality.

Data Strategy:
Understands, articulates, and applies principles of the defined strategy to routine business problems that involve a single function.
Analytical Modeling:

  • Selects the analytical modeling technique most suitable for the structured, complex data and develops custom analytical models.
  • Conducts exploratory data analysis activities (for example, basic statistical analysis, hypothesis testing, statistical inferences) on available data.
  • Defines and finalizes features based on model responses and introduces new or revised features to enhance the analysis and outcomes.
  • Identifies the dimensions of the experiment, finalizes the design, tests hypotheses, and conducts the experiment.
  • Perform trend and cluster analysis on data to answer practical business problems and provide recommendations and key insights to the business.
  • Mentors and guides junior associates on basic modeling and analytics techniques to solve complex problems.

Model Deployment & Scaling:

  • Supports efforts to ensure that analytical models and techniques used can be deployed into production.
  • Supports evaluation of the analytical model. Supports the scalability and sustainability of analytical models.
  • Code Development & Testing: Writes code to develop the required solution and application features by using the recommended programming language and leveraging business, technical, and data requirements.
  • Test the code using the recommended testing approach.

Problem Formulation:

  • Translates business problems within one's discipline to data related or mathematical solutions. Identifies what methods (for example, analytics, big data analytics, automation) would provide a solution for the problem.
  • Shares use cases and gives examples to demonstrate how the method would solve the business problem.

Model Assessment & Validation:
Supports model fit testing and statistical inferences to evaluate performance. Assesses the impact of variables and features on model performance.

Data Visualization:

  • Generates appropriate graphical representations of data and model outcomes under guidance.
  • Supports the understanding of customer requirements and designs data representations for simple data sets.
  • Presents to and influences the team using the appropriate frameworks and conveys messages through basic business understanding.
  • Demonstrates up-to-date expertise and applies this to the development, execution, and improvement of action plans by providing expert advice and guidance to others in the application of information and best practices; supporting and aligning efforts to meet customer and business needs; and building commitment for perspectives and rationales.
  • Provides and supports the implementation of business solutions by building relationships and partnerships with key stakeholders; identifying business
  • needs; determining and carrying out necessary processes and practices; monitoring progress and results; recognizing and capitalizing on improvement opportunities; and adapting to competing demands, organizational changes, and new responsibilities.
  • Models compliance with company policies and procedures and supports company mission, values, and standards of ethics and integrity by incorporating these into the development and implementation of business plans; using the Open Door Policy; and demonstrating and assisting others with how to apply these in executing business processes and practices.

Competencies:

  • Problem Formulation – Analytics, big data analytics, and/or automation techniques and methods.
  • Business requirements and insights that the business is seeking.
  • Precedence and use cases.
  • Applied Business Acumen – Industry and environmental factors (for example, market fluctuations, changes in regulatory policies or politics, emerging
  • technology, cultural practices).
  • Business practices across one domain such as finance, marketing, sales, technology, business systems, or human resources.
  • Data Source Identification – Functional business domain and scenarios. Categories of data and where it is held.
  • Business data requirements.
  • Database technologies and distributed datastores (e.g. SQL, NoSQL). Data Quality.
  • Analytical Modeling – Feature relevance and selection.
  • Exploratory data analysis methods and techniques.
  • Advanced statistical methods and best practice of advanced modelling techniques (e.g., graphical models, Bayesian inference, basic level of NLP, Vision, neural networks, SVM, Random Forest etc.).
  • Multivariate calculus.
  • Statistical models behind standard ML models.
  • Advanced excel techniques and Programming languages like R/Python.
  • Basic classical optimization techniques (e.g., Newton-Rapson methods, Gradient descent).
  • Numerical methods of optimization (e.g. Linear Programming, Integer Programming, Quadratic Programming, etc.).
  • Model Assessment & Validation – Model fit testing, tuning, and validation techniques (e.g., Chi square, ROC curve, root mean square error etc.).
  • Impact of variables and features on model performance.
  • Model Deployment & Scaling – Impact of variables and features on model performance. Understanding of servers, model formats to store models.
  • Code Development & Testing – Coding languages like SQL, Java, C++ and others. Testing methods such as static, dynamic, software composition analysis, manual penetration testing.
  • Data Visualization – Visualization guidelines. Simple data visualization tools (e.g. Excel, PowerBI, Tableau, etc.). 1-2 story plots and structures (e.g.
  • OABCDE)
  • Data Strategy – Appropriate application and understanding of data ecosystem, including Data Management, Data Quality Standards and Data
  • Governance, Accessibility, Storage and Scalability etc.
  • Customer/Member Centered: Meet Internal and External Customer/Member Needs – Identifies the requirements, expectations, and needs of customers/members.
  • Supports and aligns with initiatives, goals, and actions focused on improving customer/member service.
  • Addresses the concerns and issues of internal and external customers/members.
  • Uses customer/member data, analyses, and insights to improve
  • customer/member-related decisions.

Judgment:

  • Demonstrate Professional Judgment – Researches and integrates relevant information and data, and uses expertise to make recommendations or decisions.
  • Identifies and applies sound, fact-based criteria in setting priorities and making decisions.
  • Uses business measures and analyses to identify improvement opportunities.
  • Probes and looks beyond symptoms to determine the root causes of problems and identify possible solutions.

Execution and Results:

  • Focus on Execution and Results – Aligns and pursues work activities to achieve the mission and business priorities of the organization.
  • Shares information, practices, and resources across functions, organizations, and locations to improve performance. Effectively uses existing processes and tools to achieve performance objectives.
  • Uses and explains major process steps to manage time, resources, and challenges
  • to meet goals.

Planning and Improvement:

  • Plan for and Improve Performance – Develops and implements plans, practices, and processes to better achieve organizational goals.
  • Develops contingency plans to manage or eliminate potential problems. Identifies and recommends ways to continually improve and streamline processes and practices.

Influence and Communicate:

  • Build Influence – Develops and presents logical, convincing reasons in support of one's perspectives and initiatives.
  • Proactively shares relevant information and timely updates with appropriate people. Listens attentively and asks questions to ensure understanding.
  • Researches information for and prepares documents and presentations that effectively convey relevant information in a timely manner.
  • Ethics and Compliance: Model Ethics and Compliance – Complies with policies and procedures. Demonstrates ethical performance. Supports efforts to enforce compliance with policies and procedures.

Adaptability:

  • Adapt Professionally – Demonstrates creativity and strength in the face of change, obstacles, and adversity.
  • Adapts to competing demands and shifting priorities.
  • Updates and shares knowledge and skills to keep current in one's area of expertise. Embraces change and supports implementation.

Build Relationships:

  • Form Relationships – Builds trusting, collaborative relationships and alliances across functional and organizational boundaries.
  • Relates to others in an accepting and respectful manner, regardless of their organizational level, personality, or background. Collaborates with people from diverse backgrounds, experiences, and functional areas to discover new perspectives.

Minimum Qualifications

  • Option 1: Bachelors degree in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 2 years' experience in an analytics or related field.
  • Option 2: Masters degree in Statistics, Economics, Analytics, Mathematics, Computer Science,
  • Information Technology or related field.
  • Option 3: 4 years' experience in an analytics or related field.

Preferred Qualifications

  • Master’s degree in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics,
  • Econometrics, or related field.
  • 5 years' experience in data science, machine learning, optimization models, or related field.
  • Successful completion of one or more assessments in Python, Spark, Scala, or R.
  • 3 years’ experience using open source frameworks (for example, scikit learn, tensorflow, torch).

Name: Dharmaveer
Title: Sr. recruiter
Intellisoft Technologies, Inc.
 
1320 Greenway Dive, #460. Irving, TX 75038
Ph. (972) 756 1212 x 128
dharma@intellisofttech.com
http://www.intellisofttech.com
 
Equal Employment Opportunity
All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by federal, state, or local law.
 
 

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