Job Location: Bengaluru, Karnataka, India
Data Scientist
As a Data Scientist, you will work on incorporating the latest technological innovations within the organization and provide thought leadership to help solve complex AI and Data Science challenges. You should be familiar with production software and highly experienced in the full Machine Learning Lifecycle. While not required, prior experience in the BFSI domain is preferred.
Exp.Level: 3-5 Yrs
Role and Responsibilities:
We are seeking Data Scientists to join our Data Science team. Team members in this role will identify and address complex business problems, design and drive the creation of new data products and analytical capabilities embedded in multiple business applications.
Qualified candidates will also gather and analyze large volumes of data, evaluate scenarios to make predictions on future outcomes and support decision making for the business. Candidates must be able to use advanced statistical data modeling techniques and tools. Lastly, candidates are expected to be able to design experiments and measure impact, synthesize and communicate insights and provide recommendations for improvement in products and processes.
In this role you will:
· Use business acumen and analytical skills to identify opportunities, estimate potential, layout strategy roadmaps to solve complex business problems
· Be responsible for using analytic techniques like Machine learning, Natural Language Processing and advanced data visualizations to improve customers’ experiences
· Deploy ML solutions in production environment
· Design statistical tests for product experiments, measure impact, derive insights and provide recommendations
· Work closely with product managers to identify and answer important product questions that help improve outcomes
· Interpret problems and provide solutions using appropriate data modeling techniques
· Develop prototypes for new data product ideas
· Design large scale models using techniques such as Linear & Logistic Regression, KNN, KMeans, SVM, Supervised & Unsupervised Learning, Decision Trees, Conjoint Analysis, Spatial models, Time-series models, Graph Algorithms, Recommender Systems and other classical Machine Learning algorithms and Deep Learning algorithms using Multilayer Perceptron, RNN, CNN and LSTM
· Utilize Natural Language Processing to analyze speech and social data
· Drive the collection of new data and the refinement of existing data
· Regularly invent new and novel approaches to problems; take initiative and break down barriers to solve problems; be recognized within team as the source of solutions
· Manipulate and analyze complex, high-volume, high-dimensionality data from multiple sources
· Bring a strong passion for empirical research and for answering hard questions with data
· Communicate complex quantitative analysis in a clear, precise, and actionable manner
· Degree in Computer Science, Data Science, Software Engineering, Computer Engineering, Electrical Engineering, Electronics Engineering, or a related field
Here’s what you’ll bring to the team:
· Degree in Computer Science, Data Science, Software Engineering, Computer Engineering, Electrical Engineering, Electronics Engineering, or a related field
· Machine Learning, Deep Learning, NLP experience and also working in Hadoop and/or Spark environment
· Knowledge in Hypothesis testing, Statistical Methods, Sampling Theory, Experimental Design
· Familiarity with common advanced analysis tools – SQL, Python, R are preferred
· Demonstrated familiarity (work experience, GitHub account) with OOP concepts. Python, Java, Scala skills is a big plus
· Ability to ask and tackle the most important analytical questions with a view on driving product impact
· A motivated, focused, and self-starter mentality with effective communication skills, and amazing follow-through
· You embrace your work and love the responsibility of being individually empowered
· Experience with digital audio signal processing and Image processing is a plus
BFSI Domain working experience is nice to have
Why Synechron:
· A highly competitive compensation and benefits package
· A multinational organization with offices in 17 global locations and the possibility to work abroad
· Short- and long-term international travel
· Well-balanced Public Holiday Calendar + Earned Leaves
· Sick & Hospitalization Leaves
· Paid Maternity Leave (ML) & Paternal Leave (PL) Plans
· Child Adoption Leave (CAL) & Bonus
· Extended Unpaid Leave (UL) Plans
· Internet Allowance (for working-from-home employees)
· Relocation Benefits
· Per-Diem allowance for Short Travel and Transfer
· Comprehensive Insurance benefits, including: Group Medical Health Insurance (INR 5L), Group Personal Accidental Insurance (INR 15L), Term Life Insurance (INR 15L), Ex-Gratia amount paid by Company (INR 25L)
· Training/Certification/Higher Education Policy
· Employee Provident Fund (EPF)
· Coaching opportunities with experienced colleagues from our FinLabs and Center of Excellences (CoE) groups
· Cutting edge projects at the world’s leading tier-one banks, financial institutions and insurance firms
· A flat and approachable organization
· Regular CSR and employee care programs
· Fun-Zones across facilities: X-Box gaming zone, pool table, fun-networking events, gym, yoga, Zumba, and aerobics classes, etc. at our facilities
· A truly diverse, fun-loving, and global work culture
Diversity & Inclusion are fundamental to our culture, and Synechron is proud to be an equal opportunity workplace and is an affirmative action employer. Our Diversity, Equity, and Inclusion (DEI) initiative ‘Same Difference’ is committed to fostering an inclusive culture – promoting equality, diversity and an environment that is respectful to all. We strongly believe that a diverse workforce helps build stronger, successful businesses as a global company. We empower our global workforce by offering flexible workplace arrangements, mentoring, internal mobility, learning and development programs.
All employment decisions at Synechron are based on business needs, job requirements and individual qualifications, without regard to the applicant’s gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
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