Lead - Data Scientist - IT

Responsibilities:

- Leadership/Supervisory Role: The Lead Data Scientist, in his/her leadership capacity oversees the strategic data modelling priorities of a team of data scientists. In this position, he/she also need to guide the team on big data and analytics model frameworks for the business benefit. He/she also regulates how the business captures, maintains, and presents analytical models and an information on a global level in order to measure performance.

-It is also the role of the Lead Data Scientist to manage the lifecycle of model development, deployment and an information in order to comply with the business requirements. The Lead Data Scientist provides expertise and consults on all major data models related initiatives inclusive of personnel recruiting, development, and retention within the business.

- In his/her leadership position, the Lead Data Scientist also plays a mentorship role to key personnel within the Data Analytics team (COE) department, assisting in the execution of their function upon request, and encouraging the constant growth in their professional skills in order for them to take up his/her functions in the future. He is responsible for the collaboration with other lead data scientists, including from Flytxt, customers and partners.

- Strategy: The Lead Data Scientist plays a leading strategic role where he defines, maintains, develop and deploy data science models and oversees how the business utilize the output of statistical models. He/she establishes the strategic direction for building the statistical models to support business requirements and optimizing how the business uses statistical models.

- The Lead Data Scientist is tasked with developing, coordinating, and implementing strategies that support the business's development plans and that capture new opportunities. He/she additionally determines how best to leverage data assets that support the business strategy. In this capacity, he/she acts as a thought leader defining the business data science modelling strategy and future roadmap.

- Analytics: The Lead Data Scientist plays an analytical role where he defines and drives all analytics and business intelligence initiatives in the Analytics department. The Lead Data Scientist defines appropriate analytical models necessary to support use cases such as customer loyalty, customer segmentation, and customer 360 degree view among others business defined use cases and leverages the power of big data analytics, artificial intelligence (AI), deep learning (DL), predictive insights and analytics.

- The Lead Data Scientist works towards enabling stellar business performance by utilizing not only the data already available to the business, but also tapping into new and innovative sources of data.Identifies new analytics trends and opportunities to drive the innovation agenda across business functions & Big Data Analytics community

- The candidate will develop statistical models on distributed platforms such as Hadoop by using modern machine learning libraries such as SparkML, Shogun, Mahout OpenNLP, etc., and working experience of Extensive use of data-mining and analytics platforms such as Python, R Studio, WEKA, KNIME, SPSS, SAS, SPSS modeler, SAS Miner, etc.,

- The candidate should also be proficient in converting the algorithmic proof of concepts into business requirement documents for product development i.e., innovative and strong analytical and algorithmic problem solvers

- Collaboration: The Lead Data Scientist plays a highly collaborative role and in this position, he/she will oversee cross-functional data governance while simultaneously ensuring adoption and adherence to data quality and process governance in the relevant collaborating departments.

- Ability to work cross functionally to deliver appropriate resolution of technical, procedural, and operational issues.The candidate is expected to play a pivotal bridging role between data scientists, technology specialists, and the business /functional experts.

- The Lead Data Scientist partners closely with business's IT leadership responsible for data analytics, custodianship, and infrastructure ensuring alignment with the Data and Analytics department avoiding conflicting activities, and availing the most efficient data analytics insights across the business. In his collaborative role, he also works with key internal and external stakeholders as well as departmental leaders and executives fostering a relationship of trust and playing an advisory role in the deployment of models and to improve model performance.

Other Duties: The Lead Data Scientist also performs similar duties as he deems fit for the proper execution of his duties and duties as delegated by the Employer.

Qualifications Required:

The Lead Data Scientist has to have a master's degree in Statistics, Machine Learning, Mathematics, Computer Science, Economics, or any other related quantitative field. An equivalent of the same in working experience is also acceptable for the position

Phd Mandatory

Experience Required:12-15 Years

Skills Required (Technical/Domain / Process Related):

- Proficiency in R, Python, WEKA, SPSS, SPSS Modeler, SAS Miner, KNIME, Ruby or Scala or equivalent statistical analysis software.

- Experience with big data tools is a plus (e.g., Hadoop, HDFS,HBase, Cassandra, PySpark, SparkR, Sparklyr, Storm, etc.,)

- Experience with industry scale data mining and/or text mining.

- Experience with capturing, managing, and processing Big Data (terabytes of data present in web logs, documents, etc).

- Familiarity with relational databases (SAP HANA, Oracle, MySQL) and non-relational databases like MongoDB or HBase/Hive, tools for distributed computation using Hadoop and Spark.

- Knowledge of software development technologies is a plus (e.g. Python, Java, C/C++, .Net)

- The candidate should also be proficient in converting algorithmic proofs of concept into products.

- Knowledge in Data Warehouse and BI concepts.

- Exceptional technical acumen with sound exposure to data manipulation tools (Excel, Access, SPSS, SAS, R, Python, Big Data Technologies) and advanced knowledge of SQL

- Data consulting background preferred with experience in a large transformation project in the telecom, banking or any modern B2C industry (Preferably related to customer engagement, customer experience or marketing)

- Solid understanding of data analysis techniques and processes

- Experience in designing/developing/deploying advanced analytical modules

Behavioral Competencies:

Analytical Skills, Decision Making, Logical Reasoning and domain knowledge of Telecommunications, BFSI, logistics, Retail, online Retail, etc.,