Position: Data Scientist
Experience: 5+ Years
About TIGI HR Solution Pvt. Ltd.
TIGI HR Solution Pvt. Ltd. is recognized as a market leader in the field of technology-based staffing. TIGI HR is widely considered as India's most trusted and sought-after recruitment brand, making it an ideal choice for businesses interested in outsourcing personnel. The company operates with the goal and vision of fostering the creation of as many leaders and employment around the globe as is reasonably feasible. TIGI HR has, in a very short amount of time, developed a large-scale firm that is sustainable over the long term. The company places a high priority on speed, scalability, and predictability in its operations, which helps it to establish and maintain long-term trust relationships with both prospective clients and existing ones.
As it keeps an eye on the newest trends and technology that are available to HR professionals, TIGI HR is constantly one step ahead of the competition. In a very short amount of time, TIGI HR utilizes AI-based Recruit Robots and TMS technology to attract a potential talent pool.
- Create highly scalable AWS micro-services utilizing cutting edge cloud technologies.
- Design and develop Big Data pipelines handling huge geospatial data.
- Bring clarity to large complex technical challenges.
- Collaborate with Engineering leadership to help drive technical strategy.
- Project scoping, planning and estimation.
- Mentor and coach team members at different levels of experience.
- Participate in peer code reviews and technical meetings.
- Cultivate a culture of engineering excellence.
- Seek, implement and adhere to standards, frameworks and best practices in the industry.
- Participate in on-call rotation.
- Bachelor’s/Master’s degree in computer science, computer engineering or relevant field.
- 5+ years of experience in software design, architecture and development.
- 5+ years of experience using object-oriented languages (Java, Python).
- Strong experience with Big Data technologies like Hadoop, Spark, Map Reduce, Kafka, etc.
- Strong experience in working with different AWS technologies.
- Excellent competencies in data structures & algorithms.
Nice to have:
- Proven track record of delivering large scale projects, and an ability to break down large tasks into smaller deliverable chunks
- Experience in developing high throughput low latency backend services
- Affinity to spatial data structures and algorithms.
- Familiarity with Postgres DB, Google Places or Mapbox APIs
What we offer
At GroundTruth, we want our employees to be comfortable with their benefits so they can focus on doing the work they love.
- Unlimited Paid Time Off
- In Office Daily Catered Lunch
- Fully stocked snacks/beverages
- 401(k) employer match
- Health coverage including medical, dental, vision and option for HSA or FSA
- Generous parental leave
- Company-wide DEIB Committee
- Inclusion Academy Seminars
- Wellness/Gym Reimbursement
- Pet Expense Reimbursement
- Company-wide Volunteer Day
- Education reimbursement program
- Cell phone reimbursement
- Equity Analysis to ensure fair pay
Roles and Responsibilities
- Managing available resources such as hardware, data, and personnel so that deadlines are met.
- Analyzing the ML and Deep Learning algorithms that could be used to solve a given problem and ranking them by their success probabilities
- Exploring data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Defining validation framework and establish a process to ensure acceptable data quality criteria are met
- Supervising the data acquisition and partnership roadmaps to create stronger product for our customers.
- Defining feature engineering process to ensure usage of meaningful features given the business constraints which may vary by market
- Device self-learning strategies through analysis of errors from the models
- Understand business issues and context, devise a framework for solving unstructured problems and articulate clear and actionable solutions underpinned by analytics.
- Manage multiple projects simultaneously while demonstrating business leadership to collaborate & coordinate with different functions to deliver the solutions in a timely, efficient and effective manner.
- Manage project resources optimally to deliver projects on time; drive innovation using residual resources to create strong solution pipeline; provide direction, coaching & training, feedbacks to project team members to enhance performance, support development and encourage value aligned behaviour of the project team members; Provide inputs for periodic performance appraisal of project team members.
Preferred Technical & Professional expertise
- Undergraduate Degree in Computer Science / Engineering / Mathematics / Statistics / economics or other quantitative fields
- At least 2+ years of experience of managing Data Science projects with specializations in Machine Learning
- In-depth knowledge of cloud analytics tools.
- Able to drive Python Code optimization; ability review codes and provide inputs to improve the quality of codes
- Ability to evaluate hardware selection for running ML models for optimal performance
- Up to date with Python libraries and versions for machine learning; Extensive hands-on experience with Regressors; Experience working with data pipelines.
- Deep knowledge of math, probability, statistics and algorithms; Working knowledge of Supervised Learning, Adversarial Learning and Unsupervised learning
- Deep analytical thinking with excellent problem-solving abilities
- Strong verbal and written communication skills with a proven ability to work with all levels of management; effective interpersonal and influencing skills.
- Ability to manage a project team through effectively allocation of tasks, anticipating risks and setting realistic timelines for managing the expectations of key stakeholders
- Strong organizational skills and an ability to balance and handle multiple concurrent tasks and/or issues simultaneously.
- Ensure that the project team understand and abide by compliance framework for policies, data, systems etc. as per group, region and local standards
- Participate in full machine learning Lifecycle including data collection, cleaning, preprocessing to training models, and deploying them to Production.
- Discover data sources, get access to them, ingest them, clean them up, and make them “machine learning ready”.
- Work with data scientists to create and refine features from the underlying data and build pipelines to train and deploy models.
- Partner with data scientists to understand and implement machine learning algorithms.
- Support A/B tests, gather data, perform analysis, draw conclusions on the impact of your models.
- Work cross-functionally with product managers, data scientists, and product engineers, and communicate results to peers and leaders.
- Mentor junior team members
Who we have in mind:
- Graduate in Computer Science or related field, or equivalent practical experience.
- 4+ years of experience in software engineering with 2+ years of direct experience in the machine learning field.
- Proficiency with SQL, Python, Spark, and basic libraries such as Scikit-learn, NumPy, Pandas.
- Familiarity with deep learning frameworks such as TensorFlow or Keras
- Experience with Computer Vision (OpenCV), NLP frameworks (NLTK, SpaCY, BERT).
- Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering).
- Understand machine learning principles (training, validation, etc.)
- Strong hands-on knowledge of data query and data processing tools (i.e. SQL)
- Software engineering fundamentals: version control systems (i.e. Git, Github) and workflows, and ability to write production-ready code.
- Experience deploying highly scalable software supporting millions or more users
- Experience building applications on cloud (AWS or Azure)
- Experience working in scrum teams with Agile tools like JIRA
- Strong oral and written communication skills. Ability to explain complex concepts and technical material to non-technical users
- You'd have to set up your own shop, work with design customers to find generalizable use cases, and build them out.
- Ability to collaborate with cross-functional teams to build and ship new features
- At least 2-5 years of experience
- Predictive Analytics – Machine Learning Algorithms, Logistics & Linear Regression, Decision Tree, Clustering.
- Exploratory Data Analysis – Data Preparation, Data Exploration, and Data Visualization.
- Analytics Tools – R, Python, SQL, Power BI, MS Excel.
- Experience with relational SQL & NoSQL databases including MySQL & MongoDB.
- Familiar with the basic principles of distributed computing and data modeling.
- Experience with distributed data pipeline frameworks like Celery, Apache Airflow, etc.
- Experience with NLP and NER models is a bonus.
- Experience building reusable code and libraries for future use.
- Experience building REST APIs.
Preference for candidates working in tech product companies
- Measure the sales effectiveness efforts using data science/app/digital nudges.
- Should be able to work on the clickstream data
- Should be well versed and willing to work hands-on various Machine Learning techniques
- Ability to lead a team of 5-6 members.
- Ability to work with large data sets and present conclusions to key stakeholders.
- Develop a clear understanding of the client’s business issue to inform the best approach to the problem.
- Root-cause analysis
- Define data requirements for creating a model and understand the business problem
- Clean, aggregate, analyze, interpret data and carry out quality analysis of it
- Set up data for predictive/prescriptive analysis
- Development of AI/ML models or statistical/econometric models.
- Working along with the team members
- Looking for insight and creating a presentation to demonstrate these insights
- Supporting development and maintenance of proprietary marketing techniques and other knowledge development projects.