• Citizen

• Full Time

• Direct Hire

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 27th Jul 2022

The Data Scientist will apply his/her strong expertise in machine learning, data mining, and information retrieval to design, prototype and build next generation advanced analytics engine and services. The Data Scientist collaborates with translators to define technical problem statement and hypothesis to test; develops efficient and accurate analytical models that mimic business decisions.

Role Responsibilities

Design, create, test and implement complex machine learning and deep learning models and algorithms that drive analytical solutions throughout the organization

Work with business managers to frame a problem, both mathematically and within the business context. Perform exploratory data analysis to gain insights about the problem

Experienced in proposing ROI based solutions to business driven by AI/ML; Be a storyteller to explain the why how of your data driven recommendations to cross-functional teams

Leverage variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks to achieve business outcomes

Leverage advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications to improve model recommendations

Conduct advanced statistical and other analysis to provide actionable insights, identify trends, and measure performance leveraging TensorFlow

Use predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes

Identify and develop long-term data science processes, frameworks, tools, and standards

Comfortable working in programming languages like SQL, Python and R, as well as with frameworks like Azure ML Ops and Azure Machine Learning; experience designing solutions in distributed teams using Version Control tools like GIT

Curate and connect external data sets for broad enterprise-wide analytic usage

Develop company A/B testing framework and test model quality

Collaborate with internal stakeholders to understand business challenges and develop analytical solutions to optimize business processes monitor outcomes

Have passion to advocate and educate on the value and importance of data driven decision making analytical methods

Mentor and guide data science team members as well as developers and QA engineers working on the products.

Basic Qualifications

5+ years of experience in software development of large-scale data infrastructure and distributed systems

5+ years of experience in data extraction, transformation, statistical analysis and data modeling

5+ years of experience developing enterprise software using Java or Python

3+ years of experience in applying Data Mining and Machine Learning techniques to solve business problems

3+ years of experience using major RDBMS, SAP, Hadoop, Spark, Elasticsearch, or similar technologies

3+ years of experience with statistical modeling tools such as R, SAS, SciKit -learn,

Bachelors degree in Computer Science, Computer Engineering, Machine Learning, or related field or equivalent experience.

Technical Skills

Experience with Azure and/or GCP cloud platform

Experience in machine learning, statistics, optimization or related fields; deeper experience in working with large data sets, simulation/ optimization or distributed computing tools is a plus

Experience working with Open CV, Deep learning experience and time series analysis

Experience with Map/Reduce, SAP, Hadoop, Hive, Spark, etc.

Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets

Coding knowledge and experience with several languages: Python, Go, Java, JavaScript, R, SQL etc.

Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.

Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.

Experience visualizing/presenting data for stakeholders using: Tableau, PowerBI, Looker, Data Studio, Shiny, D3, ggplot,etc .

Professional Skill Requirements

Strong leadership and management skills

Strong communication and interpersonal skills

Strong analytical and problem-solving skills and passion for product development

Strong understanding of Agile methodologies and open to working in agile environments with multiple stakeholders

Professional attitude and service orientation; team player

Ability to translate business needs into potential analytics solution

Strong work ethic; ability to work at an abstract level and gain consensus

Ability to build a sense of trust rapport to create a comfortable effective workplace